Is there a better way to select rows from a pandas DataFrame based on multiple conditions?

Question

I'm trying to select rows from a pandas DataFrame based on multiple conditions. The code looks like this:

row = videos_train_df[
             (videos_train_df['pid1']==pid1)
            &(videos_train_df['pid2']==pid2)
            &(videos_train_df['vid'] ==vid)]

Is there any better way (in terms of code readability) to do the same thing?

Do you find that difficult to read? I don't, especially the way you've spaced it. I think the meaning is quite clear. — Tim Roberts
– Tim Roberts, Commented Dec 23, 2021 at 21:54
@Tim Roberts this particular example isn't too difficult to read, but df.query is a nice way to avoid reusing the videos_train_df variable name in the condition. Plus there could be 100 conditions instead of 3 conditions and then passing a string to df.query is easier to work with — Derek O
– Derek O, Commented Dec 23, 2021 at 21:57

Andrea Di Iura · Accepted Answer · 2021-12-23 21:55:03Z

3

You can use query

row = videos_train_df.query(
    f"pid1 == {pid1} and pid2 == {pid2} and vid == {vid}"
)

2 Comments

Tim Roberts Over a year ago

That doesn't need quoting?

Abdulwahab Almestekawy Over a year ago

Thanks, this is what I was looking for

BENY · Accepted Answer · 2021-12-23 22:05:43Z

0

I will do all after eq

new = df[df[['pid1','pid2','vid']].eq([pid1,pid2,vid]).all(1)]

answered Dec 23, 2021 at 22:05

BENY

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