如何在pandas中将字符串转换为弧度来计算两点之间的距离

import pandas as pd
import math

# 创建包含经纬度字符串的DataFrame
data = {'location': ['40.7128° N, 74.0060° W', '37.7749° N, 122.4194° W']}
df = pd.DataFrame(data)

# 函数：将经纬度字符串转换为弧度
def convert_to_radians(coord_str):
    # 提取度数和方向
    degrees, direction = coord_str.split('° ')
    degrees = float(degrees)
    
    # 根据方向判断正负
    if direction in ['S', 'W']:
        degrees = -degrees
    
    # 将度数转换为弧度
    radians = math.radians(degrees)
    return radians

# 函数：计算两点之间的距离（使用Haversine公式）
def calculate_distance(row):
    lat1, lon1 = row['location1']
    lat2, lon2 = row['location2']
    
    # 使用Haversine公式计算距离
    dlat = lat2 - lat1
    dlon = lon2 - lon1
    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  # 6371是地球的平均半径
    
    return distance

# 分割经纬度字符串，转换为弧度
df['location'] = df['location'].str.replace('°', '')  # 去除度数符号
df['location'] = df['location'].str.replace(' ', '')  # 去除空格
df['location'] = df['location'].str.replace('N', ',N')  # 标记北纬
df['location'] = df['location'].str.replace('S', ',S')  # 标记南纬
df['location'] = df['location'].str.replace('E', ',E')  # 标记东经
df['location'] = df['location'].str.replace('W', ',W')  # 标记西经
df['location'] = df['location'].str.split(',')

# 将字符串经纬度转换为弧度
df['location'] = df['location'].apply(lambda x: [convert_to_radians(coord) for coord in x])

# 创建新的列存储转换后的经纬度
df[['latitude', 'longitude']] = pd.DataFrame(df['location'].tolist(), index=df.index)

# 计算两点之间的距离
df['distance'] = df.apply(calculate_distance, axis=1)

print(df)