对四列执行haversine函数，将其转换为新列

import math

def haversine(lon1, lat1, lon2, lat2):
    # 将经纬度转换为弧度
    lon1, lat1, lon2, lat2 = map(math.radians, [lon1, lat1, lon2, lat2])

    # 应用haversine公式计算距离
    dlon = lon2 - lon1
    dlat = lat2 - lat1
    a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1-a))
    distance = 6371 * c  # 地球半径为6371公里

    return distance

import pandas as pd

# 读取数据集
data = pd.read_csv('your_dataset.csv')

# 使用apply函数将haversine函数应用于每一行数据，并创建一个新列来存储距离
data['distance'] = data.apply(lambda row: haversine(row['经度1'], row['纬度1'], row['经度2'], row['纬度2']), axis=1)

# 打印结果
print(data)