如何对数据框中位于 geopandas 边界内的条目数求和

Question

我有两个地理数据框：一个包含名为 bird_df 的特定物种动物的目击数据（以位置为点），另一个详细说明了我所在州内每个城市的边界，名为 map_df >。

我想使用 geopandas 方法 .contains(x) 来计算每个城市中发现的动物数量，并将总数添加到边界数据框中，以便我可以生成分区统计图。

我的熊猫有点生锈了，但我尝试过类似的事情 map_df[map_df["geometry"].contains(bird_df["geometry"]) == True]

我只是不知道如何解决这个问题。一些帮助将不胜感激。

谢谢

Answer 1

我建议为此使用 sjoin。

import geopandas as gpd
import pandas as pd

# make some dummy points
df = pd.DataFrame()
df['x'] = [0.61, 0.62, 0.63, 0.64, 0.65]
df['y'] = [41.60, 41.62, 41.63, 41.64, 41.65]
points_gdf = gpd.GeoDataFrame(geometry=gpd.points_from_xy(df.x, df.y))

# buffer 2 rows of points to make some dummy polys
poly_gdf = points_gdf.head(2).copy(deep=True)
poly_gdf['geometry'] = poly_gdf['geometry'].buffer(0.02)

# do the spatial join, index right is the polygon idx values
sjoin_gdf = gpd.sjoin(points_gdf, poly_gdf)

# count the values with value counts
count_dict = sjoin_gdf['index_right'].value_counts().to_dict()

# map the count_dict back to poly_gdf as new point count column 
# alternatively you could do a join here, but new col name is nice
poly_gdf['point_count'] = poly_gdf.index.map(count_dict)

输出poly_gdf：

    geometry                                            point_count
0   POLYGON ((0.63000 41.60000, 0.62990 41.59804, ...   1
1   POLYGON ((0.64000 41.62000, 0.63990 41.61804, ...   2

即：

cat_df = pd.concat([points_gdf, poly_gdf])
cat_df.plot(facecolor="none")