Space complexity of the following algorithm

Can someone explain to me the space complexity of the following code?

def countBinarySubstrings(s):
    groups = [1]
    for i in range(1, len(s)):
        if s[i-1] != s[i]:
            groups.append(1)
        else:
            groups[-1] += 1
    ans = 0
    for i in range(1, len(groups)):
        ans += min(groups[i-1], groups[i])
    return ans

print(countBinarySubstrings('110010'))

Since I am creating a new list, I think the space complexity is O(n) but I am not sure.