geopandas 颜色最接近的形状相同的颜色

Question

我有一个 geopandas 文件，其中包含 100 多个多边形和一个稀疏集（其中约 10 个）具有感兴趣的值。我有没有一种简单的方法可以根据最近的非零多边形的值为剩余的 90 多个多边形分配一个值？

提前谢谢你

Answer 1

下面的代码表示一种算法，该算法将使用基于质心的空间连接（最近邻）将“无值”多边形与具有有效值的最近多边形连接起来。

请注意，代码是您需要的代码草稿；它表示一般算法，但您需要根据您的数据和变量完成功能。

# gdf with all the polygons
gdf1 = gpd.read_file(...)

# calculate a column with the centroid geometry; 
# it will be used later.
# note: this is not the active gdf geometry at this stage
gdf1['geometry_pt'] = gdf1['geometry'].centroid

# set the point geometry as the active geometry
gdf1.set_geometry('geometry_pt')

# filter out the gdf in two gdfs, with/without the value you want
gdf1_yesval = gdf1.loc[gdf1['field1'] != 0]
gdf1_noval  = gdf1.loc[gdf1['field1'] == 0]

# perform a spatial join to assign the closest value to the points with no value
# for this, apply the code in the link below
gdf1_noval_joined = gdf1_noval.apply(...  nearest... gdf1_yesval... )

# do the necessary column operations in the joined gdf 
# to update your desired columns with values from the spatially joined gdf
gdf1_noval_joined['field1'] = gdf1_noval_joined['joinedfieldA']

# delete the unnecessary columns in the joined gdf
gdf1_noval_joined.drop(columns=['joinedfieldA', 'joinedfieldB'], inplace=True)

# concatenate the two gdfs to make one
df2 = pd.concat([gdf1_yesval, gdf1_noval_joined])

# convert it into a gdf again
gdf2 = gpd.GeoDataFrame(df2, geometry='geometry')

最近邻连接函数的解释链接是：https://gis.stackexchange.com/q/222315/93912

希望对你有帮助。