Geopandas Dataframe指向多边形

Question

我有一个由一个id和一个由2D点填充的几何列组成的geopandas数据框。我想加入每个唯一ID的点来创建一个多边形，以便我的新数据框将具有多边形作为其几何。我的代码目前看起来是这样的：

polygons = geopandas.GeoDataFrame() 
for i in id: 
    group = df[df['id']== i] 
    polygon = {'type': 'Polygon', 'coordinates': group['geometry']} 
    polygon['poly'] = polygon 
    polygons = geopandas.concat([polygon,polygons]) 

它创建了一个多边形，但是当我分配一个新的变量poly它说

ValueError: Length of values does not match length of index" 

这是有道理的，因为它仍然只是一个坐标，而不是名单一个实际的多边形对象。有谁知道如何让这个实际的多边形对象，我可以添加到一个地域和列上的列df？
在此先感谢:)

Answer 1

我已经实现了与groupby函数类似的东西。假设你的点实际上是Shapely Point对象，并按正确的顺序排序，你可以尝试这样的事情。

import pandas as pd 
import geopandas as gp 
from shapely.geometry import Point, Polygon 

# Initialize a test GeoDataFrame where geometry is a list of points 
df = gp.GeoDataFrame([['box', Point(1, 0)], 
         ['box', Point(1, 1)], 
         ['box', Point(2,2)], 
         ['box', Point(1,2)], 
         ['triangle', Point(1, 1)], 
         ['triangle', Point(2,2)], 
         ['triangle', Point(3,1)]], 
        columns = ['shape_id', 'geometry'], 
        geometry='geometry') 

# Extract the coordinates from the Point object 
df['geometry'] = df['geometry'].apply(lambda x: x.coords[0]) 

# Group by shape ID 
# 1. Get all of the coordinates for that ID as a list 
# 2. Convert that list to a Polygon 
df = df.groupby('shape_id')['geometry'].apply(lambda x: Polygon(x.tolist())).reset_index() 

# Declare the result as a new a GeoDataFrame 
df = gp.GeoDataFrame(df, geometry = 'geometry') 

df.plot() 

Answer 2

大答案@ atkat12。但是，根据您的情节，最后两个箱点应该在（0,1）和（0,0）：

# Initialize a test GeoDataFrame where geometry is a list of points 
    df = gp.GeoDataFrame([['box', Point(1, 0)], 
        ['box', Point(1, 1)], 
        ['box', Point(0,1)], 
        ['box', Point(0,0)], 
        ['triangle', Point(1, 1)], 
        ['triangle', Point(2,2)], 
        ['triangle', Point(3,1)]], 
       columns = ['shape_id', 'geometry'], 
       geometry='geometry')