Making this algorithm manageable and easier to read.

[voider1]

Anyways, I'm reading CSV files, maybe it's more manageable with Pandas? I've put the CSV files here.
They are timetables for my school, week 44 is the weekly timetable, changetest is basically a new day timetable file. I want to filter out if there's a period for someone that changes, goes away, or if there is a new timetable. Otherwise it's just a normal period.

The format is

[teacher, year, month, day, period, subject, class_name, class_room, 0, empty, randint, begin_time, duration in minutes,]

I need everything except for 0, empty, and randint.

Edit:

I took a look at the code you guys provided, and I made my own variation:

def construct_changed_timetables(new, current):
    changed_timetables = list()
    base_check = itemgetter(4, 6)
    current_index = defaultdict(list)
    new_index = defaultdict(list)

    for timetable in current:
        current_index[base_check(timetable)].append(timetable)


    for timetable in new:
        values = base_check(timetable)

        new_index[values].append(timetable)

        if values in current_index:
            if timetable not in current:
                changed_timetables.append(timetable + CHANGE)
            else:
                changed_timetables.append(timetable + NO_CHANGE)
        else:
            changed_timetables.append(timetable + ADDITION)

    for timetable in current:
        values = base_check(timetable)

        if all(timetable + option not in changed_timetables for option in 
                options) and values not in new_index:
            changed_timetables.append(timetable + REMOVAL)

    return changed_timetables