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 can filter out 0 values by query and get index of minimal value by idxmin, last select by loc:

s = df.loc[df.query('time != 0')['time'].idxmin()]
print (s)
x       240.0
y        19.0
time      9.7
Name: 3, dtype: float64

df = df.loc[[df.query('time != 0')['time'].idxmin()]]
print (df)
     x   y  time
3  240  19   9.7