python - Checking which rows contain a value efficiently -

i trying write function checks presence of value in row across columns. have script iterating through columns, worried inefficient when used on large datasets.

here current code:

import pandas pd  = [1, 2, 3, 4] b = [2, 3, 3, 2] c = [5, 6, 1, 3] d = [1, 0, 0, 99]  df = pd.dataframe({'a': a,                   'b': b,                   'c': c,                   'd': d})  cols = ['a', 'b', 'c', 'd'] df['e'] = 0 col in cols:     df['e'] = df['e'] + df[col] == 1 print(df) 

result:

    b  c   d      e 0  1  2  5   1   true 1  2  3  6   0  false 2  3  3  1   0   true 3  4  2  3  99  false 

as can see, column e keeps record of whether value "1" exists in row. wondering if there better/more efficient way of achieving these results.

you can check if values in data frame 1 , see if true in row (with axis=1):

df['e'] = df.eq(1).any(1) df #     b   c   d   e #0  1   2   5   1   true #1  2   3   6   0   false #2  3   3   1   0   true #3  4   2   3   99  false