How to apply euclidean distance function to a groupby object in pandas dataframe?

Question

I have a set of objects and their positions over time. I would like to get the average distance between objects for each time point. An example dataframe is as follows:

Answer 1

You could also use the itertools package to define your own function as follow:

 import itertools
 import numpy as np

 def combinations(series):
        l = list()
        for item in itertools.combinations(series,2):
            l.append(((item[0] - item[1])**2))
        return l

df2 = df.groupby('time').agg(combinations)
df2['avg_distance'] = [np.mean(np.sqrt(pd.Series(df2.iloc[k,0]) + 
pd.Series(df2.iloc[k,1]))) for k in range(len(df2))]

df2.avg_distance.to_frame()

Then, the output is:

    avg_distance
time    
0   1.550094
1   10.049876
2   53.037722