We have two lists:

print l 
print s

Now, I am try to see if each 2nd-level list of s has fuzzy match to any of items in list l:

print s2
for i in range(len(s)):
    for j in range(len(s[i])):

        for x in l:
            if s[i][j].find(x)>=0:
                print s[i][j]


    matchlist2.append(all(x for x in matches[i]))
print matches
print matchlist2

This gives me what was intended. But I am not happy with how it has so many loops. I am also working with pandas and if there is pandas solution that will be great to. In pandas, there are just two columns of two dataframes.

[[True, True, True], [True, False, True], [True, True, True], [True, False, True], [True, True], [True, False], [True, True, True, False]]

[True, False, True, False, True, False, False]

Extract this into functions

You are doing one well defined thing (finding fuzzy matches), so this should be at least one function, but I suggest more because you are returning two results.

Write automatic tests

Re-factoring is very hard without tests, re-running and checking the input manually is very time consuming, an automatic test runs in milliseconds.

Use the list comprehensions and zip

You are basically checking the single-dimensional list (xs) against each row of the two-dimensional list (matrix) and seeing which elements are contained and which are not. This can be expressed very easily in code.

def fuzzy_matches(xs, matrix):
    >>> list(fuzzy_matches(["a","b","c"], [["a", "b43", "x"], ["w", "b", "5cfg"]]))
    [[True, True, False], [False, True, True]]
    return ([i in j for i, j in zip(xs, line)] for line in matrix)
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