Python：如何将字典列表转换为 geopandas 数据框？

目前尚不清楚您希望如何将坐标存储在几何列中。

在以下代码中，我使用 geometry 中的 shapely 将它们转换为 POLYGON。

import pandas as pd
from shapely import geometry

mylist = [{'properties': {'raster_val': 159.6666717529297},'geometry': {'type': 'Polygon','coordinates': [[(0.016648035783361492,5.810164488393165),(0.016648035783361492,5.801840470501484),(0.024972053675042183,5.810164488393165)]]}},{'properties': {'raster_val': 176.6071014404297},'coordinates': [[(0.024972053675042183,(0.033296071566722985,5.810164488393165)]]}}]

myDic = {polY['properties']['raster_val']: geometry.Polygon(polY['geometry']['coordinates'][0]) for poly in mylist}

df = pd.DataFrame.from_Dict(myDic,orient='index').reset_index()

df.columns = ['raster_val','geometry']

print(df)

   raster_val                                           geometry
0  159.666672  POLYGON ((0.01664803578336149 5.81016448839316...
1  176.607101  POLYGON ((0.02497205367504218 5.81016448839316...

你可以这样解析：

import pandas as pd
from shapely.geometry import Polygon

data = [{'properties': {'raster_val': 159.6666717529297},5.810164488393165)]]}}]

parsed_data = [[item['properties']['raster_val'],Polygon(item['geometry']['coordinates'][0])] for item in data]
print(pd.DataFrame(data=parsed_data,columns=['raster_val','geometry']))

输出：

   raster_val                                           geometry
0  159.666672  POLYGON ((0.01664803578336149 5.81016448839316...
1  176.607101  POLYGON ((0.02497205367504218 5.81016448839316...