使用 GeoJSON 作图

在 Python 中可视化地理空间数据

Mary van Valkenburg

Data Science Program Manager, Nashville Software School

社区 GeoJSON

{ "type": "FeatureCollection",
  "features": [
    { "type":"Feature",
      "properties":{
    "name":"Historic Buena Vista"
    },"geometry":{
        "type":"MultiPolygon","coordinates":[[[[-86.79511056795417,36.17575....

neighborhoods = gpd.read_file('./data/neighborhood_boundaries.geojson')
neighborhoods.head(1)

        name             geometry
Historic Buena Vista    (POLYGON ((-86.79511056795417 36.17575964963348...)))

GeoPandas 依赖

栅格与矢量表示

Fiona
- 提供 OGR 的 Python API
GDAL/OGR
- GDAL：栅格数据转换
- OGR：矢量数据转换

栅格 vs 矢量

科孚岛的栅格图像

科孚岛的矢量图像

配色图（Colormaps）

Matplotlib 分类配色图

https://matplotlib.org/users/colormaps.html

带颜色的作图

school_districts.head(3)

first_name     last_name    position    district      geometry
Sharon         Gentry       Member       1    (POLYGON ((-86.771 36.383)...))
Jill           Speering     Vice-Chair   3    (POLYGON ((-86.753 36.404)...))
Jo Ann         Brannon      Member       2    (POLYGON ((-86.766 36.083)...))

比较配色映射

council_dists.plot(
                   column='district', 
                   cmap='Set3', 
                   legend=True)
plt.title('Council Districts')
plt.show();

带长图例的议会选区图

leg_kwds={'title':'District Number', 
          'loc': 'upper left', 
          'bbox_to_anchor':(1, 1.03), 
          'ncol':3}
council_dists.plot(column='district', 
                   cmap='Set3',
                   legend=True, 
             legend_kwds=leg_kwds)
plt.title('Council Districts')
plt.show();

带多列图例的议会选区图

Passons à la pratique !

在 Python 中可视化地理空间数据