Pandas Dataframe - find the row with minimum value based on two columns but greater than 0

Question

I have a dataframe with 3 columns: x, y, time. There are a few thousand rows.

What I want to do is retrieve the row with the minimum time but I would like that the minim

Answer 1

You don't need groupby at all. Here's an option with mask/where + loc + idxmin;

df.loc[[df.time.mask(df.time.eq(0)).idxmin()]]

Or,

df.loc[[df.time.where(df.time.ne(0)).idxmin()]]

     x   y  time
3  240  19   9.7