我正在制作一张地图，该地图需要参考点以及城市名称和州名称（巴西和哥伦比亚）的标签。从“自然地球”页面中的网络图像可以看出，功能“ populated_places”将满足我的需求。我只需要知道如何使用它即可。
在代码中，我有以下内容：
import cartopy.feature as cf
pop = cf.NaturalEarthFeature(category='cultural',
name='populated_places',
scale='10m',
facecolor='none')
该部分似乎正在工作，因为未给我任何错误或警告。
之后，我尝试使用以下方法将其绘制在地图中：
ax1.scatter('pop.LATITUDE', 'pop.LONGITUDE', projection=ccrs.PlateCarree())
AttributeError Traceback (most recent call last)
<ipython-input-4-47ca7f66b91e> in <module>
19 ax1.add_feature(stt, edgecolor='black',facecolor='none')
20 ax1.add_feature(stt_prv, linewidth=0.5, edgecolor='gray')
---> 21 ax1.scatter('pop.LATITUDE', 'pop.LONGITUDE', projection=ccrs.PlateCarree())
22
23 # ax1.add_feature(cartopy.feature.LAND)
C:\ProgramData\Anaconda3\lib\site-packages\cartopy\mpl\geoaxes.py in scatter(self, *args, **kwargs)
1435 '(PlateCarree or RotatedPole).')
1436
-> 1437 result = matplotlib.axes.Axes.scatter(self, *args, **kwargs)
1438 self.autoscale_view()
1439 return result
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\__init__.py in inner(ax, data, *args, **kwargs)
1808 "the Matplotlib list!)" % (label_namer, func.__name__),
1809 RuntimeWarning, stacklevel=2)
-> 1810 return func(ax, *args, **kwargs)
1811
1812 inner.__doc__ = _add_data_doc(inner.__doc__,
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in scatter(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, **kwargs)
4298 )
4299 collection.set_transform(mtransforms.IdentityTransform())
-> 4300 collection.update(kwargs)
4301
4302 if colors is None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in update(self, props)
914
915 with cbook._setattr_cm(self, eventson=False):
--> 916 ret = [_update_property(self, k, v) for k, v in props.items()]
917
918 if len(ret):
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in <listcomp>(.0)
914
915 with cbook._setattr_cm(self, eventson=False):
--> 916 ret = [_update_property(self, k, v) for k, v in props.items()]
917
918 if len(ret):
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in _update_property(self, k, v)
910 func = getattr(self, 'set_' + k, None)
911 if not callable(func):
--> 912 raise AttributeError('Unknown property %s' % k)
913 return func(v)
914
AttributeError: Unknown property projection
这是一个可以正确绘制代码的代码。
%matplotlib inline
import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cf
import cartopy.io.shapereader as shpr
# Retriving the information from web
stt = cf.NaturalEarthFeature(category='cultural',
name='admin_0_boundary_lines_land',
scale='10m',facecolor='none')
stt_prv = cf.NaturalEarthFeature(category='cultural',
name='admin_1_states_provinces_lines',
scale='10m',facecolor='none')
fname = shpr.natural_earth(resolution='10m', category='cultural', name='populated_places')
reader = shpr.Reader(fname)
# Image desing
fig = plt.figure(figsize=(15, 6))
# Main Map
ax = fig.add_subplot(1, 5, (1,4), projection=ccrs.PlateCarree())
ax.set_title('Populated places of the world', fontsize=16)
ax.coastlines()
points = list(reader.geometries())
ax.scatter([point.x for point in points],
[point.y for point in points],
transform=ccrs.PlateCarree(),
s=0.1, c='r')
ax.add_feature(stt, linewidth=0.2, edgecolor='black')
# Brazil Map
ax = fig.add_subplot(2, 5, 5, projection=ccrs.PlateCarree())
ax.set_extent([-74, -34, -30, 6.1])
ax.set_title('Populated places of BRA', fontsize=8)
ax.coastlines()
points = list(reader.geometries())
ax.scatter([point.x for point in points],
[point.y for point in points],
transform=ccrs.PlateCarree(),
marker='p',s=10, c='r')
ax.add_feature(stt, linewidth=0.5, edgecolor='black')
ax.add_feature(stt_prv, linewidth=0.2, edgecolor='black')
# Colombia Map
ax = fig.add_subplot(2, 5, 10, projection=ccrs.PlateCarree())
ax.set_extent([-65, -80, -5, 13])
ax.set_title('Populated places of COL', fontsize=8)
ax.coastlines()
points = list(reader.geometries())
ax.scatter([point.x for point in points],
[point.y for point in points],
transform=ccrs.PlateCarree(),
marker='p',s=10, c='r')
ax.add_feature(stt, linewidth=0.5, edgecolor='black', zorder=0)
ax.add_feature(stt_prv, linewidth=0.2, edgecolor='black', zorder=5)
plt.show()
