如何通過Python中的geoid過濾geojson文件？

Question

我有一個包含紐約所有城市坐標的 geojson 文件。 我想為紐約市創建一個 plot。 如何使用 Python 通過大地水准面訪問紐約市的坐標？

我在黑暗中嘗試了以下操作，但它不起作用。

selected_city = shape_geojson[shape_geojson['features']['properties']['geoid'] == location]

其中 location 是紐約市的大地水准面，shape_geojson 是包含紐約所有城市的文件。

謝謝

geojson文件的片段：

    {
  "type": "FeatureCollection",
  "features": [
    {
      "type": "Feature",
      "geometry": {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -73.743737,
              42.677112
            ],
            [
              -73.745489,
              42.670923
            ],
            [
              -73.743362,
              42.665549
            ],
            [
              -73.744124,
              42.663822
            ],
            [
              -73.743899,
              42.662171
            ],
            [
              -73.74166,
              42.660655
            ],
            [
              -73.74283,
              42.658936
            ],
            [
              -73.739429,
              42.656803
            ],
            [
              -73.730864,
              42.663279
            ],
            [
              -73.724964,
              42.670179
            ],
            [
              -73.723263,
              42.672879
            ],
            [
              -73.72619,
              42.673994
            ],
            [
              -73.743117,
              42.679323
            ],
            [
              -73.743737,
              42.677112
            ]
          ]
        ]
      },
      "properties": {
        "geoid": "14000US36001000100",
        "name": "Census Tract 1, Albany, NY",
        "B19013001": 32389,
        "B19013001, Error": 12524
      }
    },
    {
      "type": "Feature",
      "geometry": {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -73.761562,
              42.660941
            ],
            [
              -73.759932,
              42.659968
            ],
            [
              -73.761745,
              42.658177
            ],
            [
              -73.758936,
              42.657615
            ],
            [
              -73.750875,
              42.652557
            ],
            [
              -73.750045,
              42.654009
            ],
            [
              -73.749265,
              42.658246
            ],
            [
              -73.744909,
              42.662593
            ],
            [
              -73.744124,
              42.663822
            ],
            [
              -73.743362,
              42.665549
            ],
            [
              -73.745489,
              42.670923
            ],
            [
              -73.743737,
              42.677112
            ],
            [
              -73.747432,
              42.675943
            ],
            [
              -73.754544,
              42.670112
            ],
            [
              -73.757285,
              42.667655
            ],
            [
              -73.756117,
              42.666067
            ],
            [
              -73.761562,
              42.660941
            ]
          ]
        ]
      },
      "properties": {
        "geoid": "14000US36001000200",
        "name": "Census Tract 2, Albany, NY",
        "B19013001": 27714,
        "B19013001, Error": 3824
      }
    },
    {
      "type": "Feature",
      "geometry": {
        "type": "Polygon",
        "coordinates": [
          [
            [
              -73.827854,
              42.696384
            ],
            [
              -73.830644,
              42.693262
            ],
            [
              -73.826398,
              42.692277
            ],
            [
              -73.820366,
              42.689707
            ],
            [
              -73.797692,
              42.676636
            ],
            [
              -73.794357,
              42.679764
            ],
            [
              -73.791654,
              42.681494
            ],
            [
              -73.78511,
              42.675781
            ],
            [
              -73.780354,
              42.671637
            ],
            [
              -73.771111,
              42.666475
            ],
            [
              -73.768212,
              42.669219
            ],
            [
              -73.776549,
              42.674177
            ],
            [
              -73.775161,
              42.676038
            ],
            [
              -73.780798,
              42.67876
            ],
            [
              -73.779046,
              42.681127
            ],
            [
              -73.771972,
              42.677627
            ],
            [
              -73.766066,
              42.673645
            ],
            [
              -73.761971,
              42.67166
            ],
            [
              -73.756276,
              42.671168
            ],
            [
              -73.754544,
              42.670112
            ],
            [
              -73.747432,
              42.675943
            ],
            [
              -73.743737,
              42.677112
            ],
            [
              -73.743117,
              42.679323
            ],
            [
              -73.751329,
              42.682088
            ],
            [
              -73.760237,
              42.684932
            ],
            [
              -73.758758,
              42.681655
            ],
            [
              -73.760831,
              42.680286
            ],
            [
              -73.765303,
              42.676379
            ],
            [
              -73.770573,
              42.678953
            ],
            [
              -73.768704,
              42.681288
            ],
            [
              -73.778006,
              42.685554
            ],
            [
              -73.778621,
              42.682985
            ],
            [
              -73.780093,
              42.681853
            ],
            [
              -73.786871,
              42.685061
            ],
            [
              -73.786575,
              42.686937
            ],
            [
              -73.792365,
              42.688278
            ],
            [
              -73.80031,
              42.689053
            ],
            [
              -73.800845,
              42.688439
            ],
            [
              -73.812687,
              42.690502
            ],
            [
              -73.816816,
              42.690936
            ],
            [
              -73.827854,
              42.696384
            ]
          ]
        ]
      },

Answer 1

最直接的方法是創建一個僅包含紐約市要素數據的新 geojson object。 只要確保包含包含特征的外部結構。

如果您包含實際數據，我可以舉例說明。