The best answer here is to use all(), which is the builtin for this situation. We combine this with a generator expression to produce the result you want cleanly and efficiently. For example:

>>> items = [[1, 2, 0], [1, 2, 0], [1, 2, 0]]
>>> all(flag == 0 for (_, _, flag) in items)
True
>>> items = [[1, 2, 0], [1, 2, 1], [1, 2, 0]]
>>> all(flag == 0 for (_, _, flag) in items)
False

Note that all(flag == 0 for (_, _, flag) in items) is directly equivalent to all(item[2] == 0 for item in items), it's just a little nicer to read in this case.

And, for the filter example, a list comprehension (of course, you could use a generator expression where appropriate):

>>> [x for x in items if x[2] == 0]
[[1, 2, 0], [1, 2, 0]]

If you want to check at least one element is 0, the better option is to use any() which is more readable:

>>> any(flag == 0 for (_, _, flag) in items)
True

You can use chain

from itertools import chain
l = [[1,2,3],[1,2,3]]
len(list(chain(*l))) # give you 6

the expression list(chain(*l)) give you flat list: [1, 2, 3, 1, 2, 3]

When number of occurrences doesn't matter, you can still use the subset functionality, by creating a set on the fly:

>>> list1 = ['a', 'c', 'c']
>>> list2 = ['x', 'b', 'a', 'x', 'c', 'y', 'c']
>>> set(list1).issubset(list2)
True

If you need to check if each element shows up at least as many times in the second list as in the first list, you can make use of the Counter type and define your own subset relation:

>>> from collections import Counter
>>> def counterSubset(list1, list2):
        c1, c2 = Counter(list1), Counter(list2)
        for k, n in c1.items():
            if n > c2[k]:
                return False
        return True
   
>>> counterSubset(list1, list2)
True
>>> counterSubset(list1 + ['a'], list2)
False
>>> counterSubset(list1 + ['z'], list2)
False

If you already have counters (which might be a useful alternative to store your data anyway), you can also just write this as a single line:

>>> all(n <= c2[k] for k, n in c1.items())
True

Like this:

>>> Cards = [[["QS","5H","AS"],["2H","8H"],["7C"]],[["9H","5C"],["JH"]],["7D"]]
>>> from compiler.ast import flatten
>>> flatten(Cards) 
['QS', '5H', 'AS', '2H', '8H', '7C', '9H', '5C', 'JH', '7D']

As, nacholibre pointed out, the compiler package is deprecated. This is the source of flatten:

def flatten(seq):
    l = []
    for elt in seq:
        t = type(elt)
        if t is tuple or t is list:
            for elt2 in flatten(elt):
                l.append(elt2)
        else:
            l.append(elt)
    return l

You can use a list comprehension with enumerate:

indices = [i for i, x in enumerate(my_list) if x == "whatever"]

The iterator enumerate(my_list) yields pairs (index, item) for each item in the list. Using i, x as loop variable target unpacks these pairs into the index i and the list item x. We filter down to all x that match our criterion, and select the indices i of these elements.

Operators like <= in Python are generally not overriden to mean something significantly different than "less than or equal to". It's unusual for the standard library does this--it smells like legacy API to me.

Use the equivalent and more clearly-named method, set.issubset. Note that you don't need to convert the argument to a set; it'll do that for you if needed.

set(['a', 'b']).issubset(['a', 'b', 'c'])