I am working on a data frame that looks like this :

             lat       lon
id_zone
0        40.0795  4.338600
1        45.9990  4.829600
2        45.2729  2.882000
3        45.7336  4.850478
4        45.6981  5.043200

I'm trying to make a Haverisne distance matrix. Basically for each zone, I would like to calculate the distance between it and all the others in the dataframe. So there should be only 0s on the diagonal. Here is the Haversine function that I use but I can't make my matrix.

def haversine(x):x.lon, x.lat, x.lon2, x.lat2 = map(radians, [x.lon, x.lat, x.lon2, x.lat2])# formule de Haversinedlon = x.lon2 - x.londlat = x.lat2 - x.lata = sin(dlat / 2) ** 2 + cos(x.lat) * cos(x.lat2) * sin(dlon / 2) ** 2c = 2 * atan2(sqrt(a), sqrt(1 - a))km = 6367 * creturn km

You can use the solution to this answer Pandas - Creating Difference Matrix from Data Frame

Or in your specific case, where you have a DataFrame like this example:

             lat       lon
id_zone
0        40.0795  4.338600
1        45.9990  4.829600
2        45.2729  2.882000
3        45.7336  4.850478
4        45.6981  5.043200

And your function is defined as:

def haversine(first, second):# convert decimal degrees to radianslat, lon, lat2, lon2 = map(np.radians, [first[0], first[1], second[0], second[1]])# haversine formuladlon = lon2 - londlat = lat2 - lata = np.sin(dlat/2)**2 + np.cos(lat) * np.cos(lat2) * np.sin(dlon/2)**2c = 2 * np.arcsin(np.sqrt(a))r = 6371 # Radius of earth in kilometers. Use 3956 for milesreturn c * r

Where you pass the lat and lon of the first location and the second location.

You can then create a distance matrix using Numpy and then replace the zeros with the distance results from the haversine function:

# create a matrix for the distances between each pair of zones
distances = np.zeros((len(df), len(df)))
for i in range(len(df)):for j in range(len(df)):distances[i, j] = haversine(df.iloc[i], df.iloc[j])
pd.DataFrame(distances, index=df.index, columns=df.index)

Your output should be similar to this:

id_zone           0           1           2           3           4
id_zone
0          0.000000  659.422944  589.599339  630.083979  627.383858
1        659.422944    0.000000  171.597296   29.555376   37.325316
2        589.599339  171.597296    0.000000  161.731366  174.983855
3        630.083979   29.555376  161.731366    0.000000   15.474533
4        627.383858   37.325316  174.983855   15.474533    0.000000