Count ocurrencies of pattern in pandas dataframe based on condition

Consider this dataframe:

pd.DataFrame(['A(3)BC(1)', 'A(2)BC(5)', 'A(1)BC(3)', 'A(2)BC(5)', 'A(4)BC(2)'], columns=['Column1'])

    Column1
0   A(3)BC(1)
1   A(2)BC(5)
2   A(1)BC(3)
3   A(2)BC(5)
4   A(4)BC(2)

Is there a way to count the number of times A has a number higher than (3) without iterating through every line of the dataframe?

>Solution :

Let’s try

out = df['Column1'].str.extract('A\((\d+)\)')[0].astype(int).gt(3).sum()

print(out)

1