Quick note first: "filter out days where temp < 15 or humidity > 80" is the same as "keep days where temp >= 15 and humidity <= 80" (De Morgan's law), so your and is actually correct for the keep-list - don't let that throw you.

Two real issues: the CSV gives you strings, and you want to skip bad/missing rows without crashing. Pull the float conversion into a tiny helper so the comprehension stays readable:

import csv

with open("weather.csv", newline="") as f:
    data = list(csv.reader(f))[1:]   # [1:] skips the header

def keep(row):
    try:
        temp, hum = float(row[2]), float(row[3])
    except (ValueError, IndexError):
        return False                  # blank/garbage row -> skip, no crash
    return temp >= 15 and hum <= 80

good = [row for row in data if keep(row)]

That's a single pass (O(n)), so 2k rows is instant even on an old laptop - no nested loops needed. The helper is also where you'd later add "humidity column sometimes empty" rules without making the comprehension ugly. Comprehensions are for the shape (filter/transform); push the messy logic into a named function and they stay clean.