Using Panda's .at function to modify multiple rows

Question

I'm a little bit confused with the usage of at. From the website:

Access a single value for a row/column label pair.

Nonetheless, I can still use it to change values in multiple rows. For instance:

df = pd.DataFrame([[0, 2, 3], [0, 2, 1], [10, 20, 30]], index=[0, 1, 2], columns=['A', 'B', 'C'])

    A   B   C
0   0   2   3
1   0   2   1
2  10  20  30

idxs = df[df.B==2].index.values
df.at[idxs, 'A'] = -33

    A   B   C
0 -33   2   3
1 -33   2   1
2  10  20  30

This will in fact change the values in both the first two rows (column A). Am I doing something wrong? Is it safe using at to change multiple rows this way?

Answer 1

Technically, .at is accessing single value for a row/column label pair and changing it one at a time. But your variable idxs is a list so it is executed for every index in the list. So the answer to your question is no, you are doing nothing wrong and yes, it is perfectly safe to use .at to change multiple rows this way.