How to calculate furthest distance in similar group

Question

Here's my data

Point     Group     Longitude       Latitude
A         1               100            101
B         1                99            102
C         1               101            101
D         1               102            101
E         2                90            103
F         2                89            105
G         2                91            104
H         2                92            103

What I need is

Group     distance    Origin      Destination
1          3.16227         B                D
2          3.60555         F                H

Notes: You can use Haversine distance for better approximation, I calculate dataframe above just using pythagorean theorem, below the Haversine equation

from sklearn.neighbors import BallTree, DistanceMetric
from math import radians, cos, sin, asin, sqrt
import pandas as pd
import numpy as np
def haversine(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in decimal degrees)
    """
    # convert decimal degrees to radians 
    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
    # haversine formula 
    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a)) 
    # Radius of earth in kilometers is 6371
    km = 6371* c
    return km

Regards

Answer 1

You may can create you own function with scipy

from scipy.spatial.distance import cdist
def yourfunc(y) :
    a = cdist(y[['Longitude', 'Latitude']], y[['Longitude', 'Latitude']], metric='euclidean')
    a_max = a.max()
    idx = np.where(a == a_max)[0]
    return pd.Series([a_max]+y['Point'].iloc[idx].tolist(),index = ['distance','Origin','Destination'])
    
df.groupby('Group').apply(yourfunc)

Out[27]: 
       distance Origin Destination
Group                             
1      3.162278      B           D
2      3.605551      F           H