Calculate the distance like the Google Maps in longitude and latitude origin and longitude and latit-CodePudding

I have the follow df with the columns:

lati_origin longi_oringin lati_final longi_final
-19.864315   -44.047180   -3.026643   -59.955860

I used the follow function, but don't return the same distance in km of Google Maps.

def haversine_np(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points
    on the earth (specified in decimal degrees)

    All args must be of equal length.    

    """
    lon1, lat1, lon2, lat2 = map(np.radians, [lon1, lat1, lon2, lat2])

    dlon = lon2 - lon1
    dlat = lat2 - lat1

    a = np.sin(dlat/2.0)**2   np.cos(lat1) * np.cos(lat2) * np.sin(dlon/2.0)**2

    c = 2 * np.arcsin(np.sqrt(a))
    km = 6371 * c
    return km

Can someone help me calculate the distance similar the Google Maps from my df?

CodePudding user response：

You can use geopy to find the distance

import geopy.distance

def calculte_distance(lon1, lat1, lon2, lat2):
    coords_1 = (lat1, lon1)
    coords_2 = (lat2, lon2)
    return geopy.distance.geodesic(coords_1, coords_2).km

Installation

pip install geopy

Execution:

In [1]: calculte_distance(-44.047180,-19.864315,-59.955860,-3.026643)
Out[1]: 2541.261913716022