具有经纬度的Pandas数据帧的行间距离矩阵

import pandas as pd
from math import radians, sin, cos, sqrt, atan2

data = {'Latitude': [lat1, lat2, lat3, ...],
        'Longitude': [lon1, lon2, lon3, ...]}
df = pd.DataFrame(data)

def calculate_distance(lat1, lon1, lat2, lon2):
    # 将经纬度转换为弧度
    lat1 = radians(lat1)
    lon1 = radians(lon1)
    lat2 = radians(lat2)
    lon2 = radians(lon2)
    
    # 应用Haversine公式计算距离
    dlon = lon2 - lon1
    dlat = lat2 - lat1
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * atan2(sqrt(a), sqrt(1-a))
    distance = 6371 * c  # 地球半径为6371公里
    
    return distance

dist_matrix = pd.DataFrame(index=df.index, columns=df.index)

for i in range(len(df)):
    for j in range(len(df)):
        lat1 = df['Latitude'][i]
        lon1 = df['Longitude'][i]
        lat2 = df['Latitude'][j]
        lon2 = df['Longitude'][j]
        distance = calculate_distance(lat1, lon1, lat2, lon2)
        dist_matrix.iloc[i, j] = distance