Adding a new column in dataframe conditionally

Question

I have a dataframe as follows:

| Time  | A     | B     |C    |
| ----  |--     | ----  |---- |
| 1.0   |    0  |   1   |  0  |
| 2.0   |    1  |   1   |  0  |
| 3.0   |    1  |   1   |  1  |
| 4.0   |    0  |   1   |  1  |
| .     |    .  |   .   |  .  |
| 1000.0|    1  |   1   |  1  |

I want to write to a new column D=1 whenever A==1 & B==1 & C==1 and 0 otherwise

Answer 1

This is a possible solution, although it might not be the more efficient:

df["D"] = ((df["A"] == 1) & (df["B"] == 1) & (df["C"] == 1)).astype(int)

This one looks better, and should return the same output as the previous one:

df["D"] = (df["A"] & df["B"] & df["C"]).astype(int)

Another option to check if each column is equal to one and then sum their values (credit to @enke for removing the binary constrain of the old version):

df["D"] = (df[["A", "B", "C"]].eq(1).sum(axis=1) == 3).astype(int)