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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?

Lucas Lazari
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2 Answers2

3

Let's try

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

print(out)

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Ynjxsjmh
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  • Worked perfectly. Is it possible to make a combination of A and B? To find A>3 and B<5? – Lucas Lazari Aug 09 '22 at 18:55
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    @LucasLazari You can similarly extract `B` times and check https://stackoverflow.com/questions/48978550/pandas-filtering-multiple-conditions. – Ynjxsjmh Aug 09 '22 at 18:58
1

If the format is always A(X) at the start, you can do:

df['Column1'].apply(lambda st: int(st[st.find("A")+2:st.find(")")])).gt(3).sum()

Output

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Yuca
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