How to calculate the distance between two locations using Haversine Formula?
I am not an expert in geometrics but I found that this function has already been supported by sklearn. So I decided to help you define a generic function.
from sklearn.metrics.pairwise import haversine_distances
from math import radians
import pandas as pd

def distance(location1, lat, lon):
  location1_radian = [radians(_) for _ in location1]
  location2 = [lat, lon]
  location2_radian = [radians(_) for _ in location2]
  result = haversine_distances([location1_radian, location2_radian])
  result = result * 6371000/1000  # multiply by Earth radius to get kilometers

  return result[0][1]

df = pd.DataFrame({
    'Latitude': [-0.123684, -0.129212, -0.123234],
    'Longitude': [51.485020, 51.507426, 52.476264]
})

df.apply(lambda x: distance([0.1245, 51.685], x.Latitude, x.Longitude),axis=1)
# 0    35.440884
# 1    34.434944
# 2    92.195943
# dtype: float64