如何将每个数据帧行与元组中的每个点进行比较，并将最近点的索引分配给新列？

import pandas as pd
import numpy as np

# 创建示例数据帧
data = {'x': [1, 2, 3, 4, 5],
        'y': [6, 7, 8, 9, 10]}
df = pd.DataFrame(data)

# 创建示例元组
points = [(2, 7), (4, 9)]

# 计算每个数据帧行与每个点的距离，并记录最近点的索引
df['closest_index'] = np.nan
for i, row in df.iterrows():
    closest_distance = float('inf')
    closest_index = -1
    for j, point in enumerate(points):
        distance = np.sqrt((row['x'] - point[0])**2 + (row['y'] - point[1])**2)
        if distance < closest_distance:
            closest_distance = distance
            closest_index = j
    df.at[i, 'closest_index'] = closest_index

print(df)