How can I convert a dictionary of polygons' coordinates to a geodataframe?

Question

I have a python dictionary looking like this:

{0: [[806735.1544109267, 6537534.445304121],
     [841214.0757437024, 6522224.452253355],
     [842501.6252045294, 6522869.442922172],
     [842549.1443712532, 6522901.510964515],
     [806735.1544109267, 6537534.445304121]],
 1: [[841408.2671391629, 6521335.689519852],
     [841100.3038260225, 6520996.388704606],
     [842331.2640584556, 6520540.411264208],
     [841950.1552972465, 6521128.964539945],
     [841408.2671391629, 6521335.689519852]],
 2: [...]}

It corresponds to multipolygons. Each polygon is defined by a number (0, 1, etc.) and a list of coordinates in 2154 (scr). My goal is to turn this dictionary into another format that I can easily manipulate ( geodataframe ), so that I could read it in GIS (as a shapefile for instance). Has anyone an idea?

Answer 1

If you want an id column and a geometry column, 'id' and 'geometry' should be the keys in your dictionary:

import geopandas as gdp

d = {
    'id': [0, 1],
    'geometry': [
        [
            [806735.1544109267, 6537534.445304121],
            [841214.0757437024, 6522224.452253355],
            [842501.6252045294, 6522869.442922172],
            [842549.1443712532, 6522901.510964515],
            [806735.1544109267, 6537534.445304121]
        ],
        [
            [841408.2671391629, 6521335.689519852],
            [841100.3038260225, 6520996.388704606],
            [842331.2640584556, 6520540.411264208],
            [841950.1552972465, 6521128.964539945],
            [841408.2671391629, 6521335.689519852]
        ],
    ]
}

gdf = gdp.GeoDataFrame(d)

More information and examples in geopandas documentation