如何使用 geopandas 对 shapefile 中的特征进行迭代连接，然后对分类数据进行编码？

Question

我有两个 shapefile (https://drive.google.com/drive/folders/1pbvKvhIIvhqHfcMe9g6qtsjbZ6SzZrqt?usp=sharing) - 一个点层和一个多边形层。点层表示客户及其位置，而多边形层表示两个边界。 objective是得到一个table，格式如下：

customer	location 1	location 2
1	1	1
2	0	1
3	1	1
5	1	0
6	1	0
9	0	0
10	0	0

我想到的方法是遍历多边形并对点进行连接，然后对类别进行编码：

import geopandas as gpd

points = gpd.read_file('point.shp')
polygons = gpd.read_file('polygon.shp')

for index,row in polygons.iterrows():
    points = gpd.sjoin(points, row, how='left', op='intersects')
    points = pd.get_dummies(points, columns=['name'])

我收到此错误消息：

ValueError: 'right_df' should be GeoDataFrame, got <class 'pandas.core.series.Series'>

感谢任何建议，提前致谢！

Answer 1

你不需要连接，intersects方法就足够了。您的目标结构可以通过以下方式实现：

points_in_locations = points.copy()
for idx, row in polygons.iterrows():
    is_in_polygon = points.intersects(row.geometry)
    points_in_locations[f"location {idx + 1}"] = is_in_polygon.astype(int)

导致：

   id                   geometry  location 1  location 2
0   1  POINT (103.87728 1.30449)           0           1
1   2  POINT (103.87723 1.30415)           0           1
2   3  POINT (103.87761 1.30408)           0           1
3   1  POINT (103.87680 1.30287)           1           0
4   5  POINT (103.87724 1.30288)           1           0
5   6  POINT (103.87710 1.30275)           1           0
6   3  POINT (103.87687 1.30270)           1           0
7   9  POINT (103.87669 1.30444)           0           0
8  10  POINT (103.87681 1.30396)           0           0

如何使用 geopandas 对 shapefile 中的特征进行迭代连接，然后对分类数据进行编码？

How can I do a sjoin iteratively over features in a shapefile with geopandas, then encode categorical data?

python

pandas

geopandas