如何选择每对列并通过熊猫代码进行迭代

Question

数据框的小部分是：

border = 

12_longitude_1  12_latitude_1   14_longitude_2  14_latitude_2   15_longitude_3  15_latitude_3
            11             12               13             14               15            16
            11             12               13             14               15            16
            11             12               13             14               15            16

我想这样做，但是在IndexError: index 3 is out of bounds for axis 0 with size 3中出现curr_lat_name = border.columns[col_num + 1]错误：

pd_out = pd.DataFrame({'zone': [], 'number': []})

for col_num in range(0, len(border.columns), 2):
    curr_lon_name = border.columns[col_num]
    curr_lat_name = border.columns[col_num + 1]
    num = curr_lon_name.split("_")[-1]
    border = border[[curr_lon_name, curr_lat_name]].dropna()
    border[curr_lon_name] = border[curr_lon_name].replace(r'[()]', '', regex=True)
    border[curr_lat_name] = border[curr_lat_name].replace(r'[()]', '', regex=True)
    border[curr_lon_name] = pd.to_numeric(border[curr_lon_name], errors='coerce')
    border[curr_lat_name] = pd.to_numeric(border[curr_lat_name], errors='coerce')
    geometry2 = [Point(xy) for xy in zip(border[curr_lon_name],border[curr_lat_name])]
    border_point = gpd.GeoDataFrame(border,crs=crs,geometry=geometry2)
    turin_final = Polygon([[p.x, p.y] for p in border_point.geometry])
    within_turin = turin_point[turin_point.geometry.within(turin_final)]
    curr_len = len(within_turin)
    pd_out = pd_out.append({'zone': "long_lat_{}".format(num), 'number': curr_len}, ignore_index=True)

所需的输出：

图书馆：

import numpy as np
import pandas as pd
import geopandas as gpd
from shapely.geometry import Point, Polygon