我试图从here读一些.GDB文件(文件夹):。
我用GeoPandas并执行以下操作:
# file from local path
mallard = gpd.read_file('./bird-species/E00039600_mallard.gdb/')
# geopandas included map, filtered to just this hemisphere
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
westhem = world[(world['continent'] == 'North America') |
(world['continent'] == 'South America')]
# making sure the coordinates line up:
mallard = mallard.to_crs(world.crs)
#establishing figure axes
base = westhem.plot(color='white', edgecolor='black',figsize=(11,11))
# cmap because I'd LIKE the multiple layers to exist
bbw_duck.plot(ax=base, cmap = 'Reds');
输出看起来是这样的:
是否有GeoPandas,或Python(Jupyter笔记本电脑)一般办法看到所有的层?
是的,GeoPandas支持层。当你的层的名称是非常长的,我建议使用层的顺序。
mallard_0 = gpd.read_file('./bird-species/E00039600_mallard.gdb/', layer=0)
mallard_1 = gpd.read_file('./bird-species/E00039600_mallard.gdb/', layer=1)
# geopandas included map, filtered to just this hemisphere
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
westhem = world[(world['continent'] == 'North America') |
(world['continent'] == 'South America')]
# making sure the coordinates line up:
mallard_0 = mallard_0.to_crs(world.crs)
mallard_1 = mallard_1.to_crs(world.crs)
# establishing figure axes
base = westhem.plot(color='white', edgecolor='black', figsize=(11, 11))
# cmap because I'd LIKE the multiple layers to exist
mallard_0.plot(ax=base, color='red', alpha=.5)
mallard_1.plot(ax=base, color='blue', alpha=.5)
编辑:Geopandas是罩用于文件处理下,使用菲奥娜,所以如果你想看到你的图层使用的列表
import fiona
fiona.listlayers('./bird-species/E00039600_mallard.gdb')
EDIT2:遍历所有图层,然后将这个样子:
import fiona
# geopandas included map, filtered to just this hemisphere
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
westhem = world[(world['continent'] == 'North America') |
(world['continent'] == 'South America')]
base = westhem.plot(color='white', edgecolor='black', figsize=(11, 11))
layers = fiona.listlayers('./bird-species/E00039600_mallard.gdb')
for l in layers:
mallard = gpd.read_file('./bird-species/E00039600_mallard.gdb', layer=l)
mallard = mallard.to_crs(world.crs)
mallard.plot(ax=base, color='red', alpha=.1)