Question

我最近开始使用GeoPandas制作地图并发现它非常有用。我已经使用了Pandas一段时间了，我发现移动到GeoPandas是相对无痛的。但是，在使用.dissolve（）函数对点进行分组后，我在绘制地图上的点时遇到问题。

基本上，我有一系列英国邮政编码数据，其中包含从国家统计邮政编码目录（ONSPD）下载的相关经度和纬度值。经度和纬度值基于CRS WGS84。我可以转换为CRS OSGB36并在地图上绘制所有点没有问题。但是，如果我使用.dissolve（）方法基于其他变量（例如＆＃39; group1＆＃39;和＆＃39; group＆＃39;）对点进行分组，我就无法再绘制点。

以下是我到目前为止所有要点的代码：

import pandas as pd
import geopandas as gif
import matplotlib.pyplot as plot
import shapely

# Define a Pandas dataframe containing postcodes and 
postcodeDF = pd.DataFrame({'pcd': ['RM175AG', 'NP181PH', 'LS8 1EN', 'HG1 1XQ', 'G11 6YB', 'TN218AB', 'GU138AL', 'CV344BD', 'YO126PH', 'SO172WT', 'PR2 8HN', 'TF1 2HD', 'M31 4FR', 'CH460UB', 'EX111LN', 'TS214DX', 'BN4 2LS', 'FY8 1XL', 'KA256BP', 'DA1 1QR'],
                           'ctry': ['E92000001', 'W92000004', 'E92000001', 'E92000001', 'S92000003', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'E92000001', 'S92000003', 'E92000001'],
                           'long': [0.320423, -2.968257, -1.51314, -1.522386, -4.309171, 0.255878, -0.8502959999999999, -1.588886, -0.41805299999999995, -1.382926, -2.699804, -2.531778, -2.425061, -3.110276, -3.317868, -1.429442, -0.22178699999999998, -3.019257, -4.686457, 0.224912],
                           'lat': [51.491329, 51.628333000000005, 53.840114, 54.002427000000004, 55.870383, 50.966097999999995, 51.275081, 52.280791, 54.296222, 50.921857, 53.780733999999995, 52.692078, 53.415147, 53.394830000000006, 50.758146, 54.680499, 50.84042, 53.753078, 55.749168999999995, 51.441911],
                           'group1':['A']*10 + ['B']*10,
                           'group2':[True,False]*10})

# Set up geodataframe, initially with CRS = WGS84 (since that matches the long and lat co-ordinates)
crs = {'init':'epsg:4326'}
geometry = [shapely.geometry.Point(xy) for xy in zip(postcodeDF['long'], postcodeDF['lat'])]

postcodeGDF = gpd.GeoDataFrame(postcodeDF,
                               crs = crs,
                               geometry = geometry)

# Convert geometry to OSGB36
postcodeGDF = postcodeGDF.to_crs(epsg = 27700)

print(postcodeGDF)

地理数据框包含以下信息：

ctry group1  group2        lat      long      pcd  \
0   E92000001      A    True  51.491329  0.320423  RM175AG   
1   W92000004      A   False  51.628333 -2.968257  NP181PH   
2   E92000001      A    True  53.840114 -1.513140  LS8 1EN   
3   E92000001      A   False  54.002427 -1.522386  HG1 1XQ   
4   S92000003      A    True  55.870383 -4.309171  G11 6YB   
5   E92000001      A   False  50.966098  0.255878  TN218AB   
6   E92000001      A    True  51.275081 -0.850296  GU138AL   
7   E92000001      A   False  52.280791 -1.588886  CV344BD   
8   E92000001      A    True  54.296222 -0.418053  YO126PH   
9   E92000001      A   False  50.921857 -1.382926  SO172WT   
10  E92000001      B    True  53.780734 -2.699804  PR2 8HN   
11  E92000001      B   False  52.692078 -2.531778  TF1 2HD   
12  E92000001      B    True  53.415147 -2.425061  M31 4FR   
13  E92000001      B   False  53.394830 -3.110276  CH460UB   
14  E92000001      B    True  50.758146 -3.317868  EX111LN   
15  E92000001      B   False  54.680499 -1.429442  TS214DX   
16  E92000001      B    True  50.840420 -0.221787  BN4 2LS   
17  E92000001      B   False  53.753078 -3.019257  FY8 1XL   
18  S92000003      B    True  55.749169 -4.686457  KA256BP   
19  E92000001      B   False  51.441911  0.224912  DA1 1QR   

                                       geometry  
0   POINT (561188.9840165515 179484.0452796911)  
1   POINT (333075.0000681121 192612.9537310874)  
2    POINT (432134.031689987 438316.9950631865)  
3    POINT (431404.026064762 456371.9915770486)  
4   POINT (255609.0244790429 666546.0027781442)  
5   POINT (558502.0104336547 120942.0242662177)  
6   POINT (480294.0287511199 153509.0281225364)  
7   POINT (428143.9880141384 264818.0084207859)  
8   POINT (503054.9928648224 490110.0245871434)  
9    POINT (443470.0222579727 113781.050039533)  
10  POINT (353983.9862037547 431827.9554603411)  
11   POINT (364154.9903684837 310620.967712217)  
12  POINT (371845.0195746602 391010.9943895991)  
13   POINT (326267.022012488 389240.9700794323)  
14   POINT (307141.054758316 96222.92213930591)  
15  POINT (436886.0245473493 531865.0198253235)  
16  POINT (525299.9996502266 106049.9600256799)  
17  POINT (332890.0335889475 429005.9677596154)  
18  POINT (231483.9972917534 653913.0284422053)  
19  POINT (554726.0039838878 173783.0302315076)

可以用来绘制地图：

# Plot map
fig, ax = plt.subplots(1,
                       figsize = (4,5),
                       dpi = 72,
                       facecolor = 'lightblue')

ax.set_position([0,0,1,1])   # Puts axis to edge of figure
ax.set_axis_off()            # Turns axis off so facecolour applies to axis area as well as bit around the outside
ax.get_xaxis().set_visible(False)   # Turns the x axis off so that 'invisible' axis labels don't take up space
ax.get_yaxis().set_visible(False)

lims = plt.axis('equal')

# N.B. Code to plot shapefile has been deleted for clarity

postcodeGDF.plot(ax=ax)

plt.show()

地图（包括shapefile大纲）如下所示：

但是，我想根据地理数据框中的其他变量对邮政编码进行分组（在本例中为变量＆＃39; group1＆＃39;和＆＃39; group2＆＃39;）（并最终绘制不同的颜色和标记对于每个小组 - 虽然我还没有那么远。我使用.dissolve（）方法对点进行分组。

postcodesGroupby = postcodeGDF.dissolve(by = ['group1','group2'])
print(postcodesGroupby)

groupby数据框如下所示：

                                                        geometry       ctry
group1 group2                                                                 
A      False   (POINT (333075.0000681121 192612.9537310874), ...  W92000004   
       True    (POINT (255609.0244790429 666546.0027781442), ...  E92000001   
B      False   (POINT (326267.022012488 389240.9700794323), P...  E92000001   
       True    (POINT (231483.9972917534 653913.0284422053), ...  E92000001   

                     lat      long      pcd  
group1 group2                                
A      False   51.628333 -2.968257  NP181PH  
       True    51.491329  0.320423  RM175AG  
B      False   52.692078 -2.531778  TF1 2HD  
       True    53.780734 -2.699804  PR2 8HN

但是，当我尝试使用以下方式绘制点数时：

postcodesGroupby.plot(ax=ax)

......地图上没有任何积分。

我怀疑我错过了一些明显的东西，但我已经盯着代码看了一会儿，再也看不到树木了。我将非常感激地收到任何关于如何解决这个问题的建议。

Answer 1

问题是此时的地理分布还不支持绘制MultiPoints（以及dissolve方法将Points分组为MultiPoints）。您获得空白图像而不是良好的错误消息这一事实有点不幸......

但是，刚刚合并了公关以增加对绘制MultiPoints的支持：https://github.com/geopandas/geopandas/pull/683。所以这将在下一个geopandas版本中发挥作用。

现在的解决方法是绘制各个点，但必须使用适当的分组颜色，以添加反映这些组的列：

# add a new column with an integer indicating the group number
postcodeGDF['group'] = postcodeGDF.groupby(['group1','group2']).ngroup()
postcodeGDF.plot(column='group', categorical=True, legend=True)

给出：

使用GeoPandas绘制地图上的点组会生成空白图像

1 个答案: