Setting values in a list to 0 based on conditions

Question

I have a dataframe of lists that look like this:

alist = ['male','male', 'male','female','male, '0', 'female','female','female','male', 'female']
        ['0','female', 'male','female','female, 'male', 'male','male','female','male',]

Now, i want to set all 'male' values nested between 'females' to zero, and vice versa, so as to have a list of non-overlapping values.

['male','male', 'male','0','male, '0', 'female','female','female','0', 'female']
['0','female', '0','female','female, 'male', 'male','male','0','male',]

I have tried this:

 for i in alist:
        rules1 = [ i == 'male',   
             i + 1 == 'female',
              i - 1 == 'female']
        rules2 = [ i == 'female',   
             i + 1 == 'male',
              i - 1 == 'male']
        if all(rules1) or all(rules2):
            i = 0
        else:
            i = i
    return alist   

fixlist_['new_tags'] = fixlist_.apply(find_start, axis=1)       

I am doing something wrong, but i cant seem to catch it. this code returns an error

----> 9              i + 1 == 'cons',
     10               i - 1 == 'cons']
     11         rules2 = [ i == 'cons',   

TypeError: ('can only concatenate str (not "int") to str', 'occurred at index 0')

Thanks all.

Answer 1

You can try this:

for i, value in enumerate(alist):
    if i>1 and i<len(alist)-1 and value == 'male' and alist[i-1] == 'female' and alist[i+1] == 'female':
        alist[i] = '0'
    if i>1 and i<len(alist)-1 and value == 'female' and alist[i-1] == 'male' and alist[i+1] == 'male':
        alist[i] = '0'
print(alist)

['male', 'male', 'male', '0', 'male', '0', 'female', 'female', 'female', '0', 'female', '0', 'female', '0', 'female', 'female', 'male', 'male', 'male', '0', 'male']