function returning list with one extra length than it should

I have data that looks like this:

data = [[['INS', 'Y', '18', '021', '28', 'A', '', '', 'AC'],
         ['REF', '0F', '816383217'],
         ['HD', '021', '', 'EPO', 'Copayment Level -1', 'IND']],
        [['INS', 'Y', '18', '024', '07', 'A', '', '', 'TE'],
         ['REF', '0F', '734419065']],
        [['INS', 'Y', '18', '024', '07', 'A', '', '', 'TE'],
         ['REF', '0F', '778954065']]]

I want to loop through it and create a pandas series of the copayment_level which is the number after the dash -. If that element does not exist in the list of lists then it should append None to the new list. I created a function to do this but the problem is it returns one extra than it should.

def copay_level():
    l = []
    for i in data:
        for lst in i:
            for x in lst:
                if x.startswith('Copayment Level'):
                    x = x.split('-')
                    l.append(x[1])
        else:
            l.append(None)
    return l

copayment_level = pd.Series(copay_level())
print(copayment_level)

0       1
1    None
2    None
3    None
dtype: object

Cant figure out why its doing this. Thanks

>Solution :

You have to avoid adding None if you found Copayment Level in the item. Use a variable to track this.

def copay_level():
    l = []
    for i in data:
        found_copay = False
        for lst in i:
            for x in lst:
                if x.startswith('Copayment Level'):
                    x = x.split('-')
                    l.append(x[1])
                    found_copay = True
        if not found_copay:
            l.append(None)
    return l

You could do this with else: if you only had one level of looping, and used break when you find a Copayment Level. But since that’s in a nested loop, else: won’t detect a break there.