在将距离矩阵合并到数据框时将 ID 分配给列名答案

【问题标题】：Assigning ID to column name in merging distance matrix to dataframe在将距离矩阵合并到数据框时将 ID 分配给列名
【发布时间】：2021-09-16 04:05:42
【问题描述】：

我遇到了这个我无法解决的问题，我希望在这里获得一些见解。

我有这个geopandas 数据框：

GEO = 
id                                      geometry_zone  \
0     A001DFD  POLYGON ((48.08793 50.93755, 48.08793 49.18650...   
1      A001DG  POLYGON ((60.96434 49.05222, 59.86796 49.29929...   
2   A001DS007  POLYGON ((53.16200 50.20131, 52.84363 48.45026...   
3    A001DS01  POLYGON ((59.04953 49.34561, 58.77158 47.52346...   
4    A001DS02  POLYGON ((58.12301 49.46915, 57.79873 47.67788...   
5    A001DS03  POLYGON ((57.07498 49.66937, 56.79702 47.84722...   
6    A001DS04  POLYGON ((56.13302 49.80835, 55.83962 48.00164...   
7    A001DS05  POLYGON ((55.16017 49.93189, 54.89766 48.18694...   
8    A001DS06  POLYGON ((54.14099 50.05542, 53.86304 48.27959...   
9    A001DS08  POLYGON ((52.22678 50.36050, 51.94821 48.52985...   
10   A001DS09  POLYGON ((50.93339 48.70894, 51.96811 48.52985...   
11   A001DS10  POLYGON ((50.23695 50.67887, 49.91857 48.84823...   
12   A001DS11  POLYGON ((50.23695 50.67887, 49.60020 50.75847...   
13   A001FS01  POLYGON ((46.47617 48.94772, 46.47617 47.63443...   
14   A001FS02  POLYGON ((46.49606 50.04213, 46.47617 48.94772...   

                     centroid  
0   POINT (48.75295 49.98494)  
1   POINT (60.27696 48.21993)  
2   POINT (53.49869 49.22928)  
3   POINT (59.29040 48.38586)  
4   POINT (58.42620 48.49535)  
5   POINT (57.43469 48.68996)  
6   POINT (56.46528 48.82210)  
7   POINT (55.50608 48.98701)  
8   POINT (54.51093 49.10232)  
9   POINT (52.52668 49.40021)  
10  POINT (51.59314 49.51614)  
11  POINT (50.57522 49.68396)  
12  POINT (49.74105 49.81923)  
13  POINT (47.00679 48.58955)  
14  POINT (47.23437 49.55921)

其中的点是geometry_zone 质心。现在，我知道如何计算每个点之间的距离，即计算距离矩阵：

GEO_distances
 0          1         2          3          4         5         6   \
0    0.000000  11.063874  4.299228  10.275246   9.312075  8.274448  7.312941   
1   10.983097   0.000000  6.348082   0.616036   1.399226  2.373198  3.374784   
2    4.132203   6.259105  0.000000   5.469828   4.507633  3.469029  2.507443   
3    9.982697   0.409114  5.348195   0.000000   0.399280  1.373252  2.374671   
4    9.112541   1.279148  4.477119   0.487986   0.000000  0.504366  1.503677   
5    8.102334   2.289412  3.468492   1.497509   0.538514  0.000000  0.494605   
6    7.124643   3.266993  2.490125   2.475753   1.515950  0.474954  0.000000   
7    6.151367   4.240258  1.517485   3.448859   2.489192  1.448060  0.487174   
8    5.151208   5.240246  0.515855   4.450013   3.488962  2.449214  1.487936   
9    3.145284   7.246023  0.481768   6.456493   5.494540  4.455695  3.494278   
10   2.205711   8.185458  1.420986   7.396838   6.433798  5.396039  4.434327   
11   1.174092   9.217045  2.452510   8.428427   7.465334  6.427628  5.465988   
12   0.329081  10.062023  3.297427   9.273461   8.310263  7.272662  6.311059   
13   1.235000  12.579303  5.838504  11.812993  10.830385  9.818336  8.852372   
14   0.853558  12.484730  5.717153  11.712257  10.730567  9.711458  8.743639   

          7         8         9         10        11         12         13  \
0   6.343811  5.312333  3.377798  2.368462  1.343153   0.675055   1.051959   
1   4.353762  5.318769  7.388784  8.269175  9.305375  10.325337  12.247130   
2   1.538467  0.506829  0.544190  1.416284  2.454398   3.479383   5.430826   
3   3.353424  4.318400  6.388838  7.269062  8.304972   9.325272  11.250890   
4   2.482659  3.447704  5.519952  6.398068  7.434796   8.456133  10.381205   
5   1.473030  2.437971  4.509526  5.388997  6.424600   7.445701   9.379809   
6   0.494829  1.459821  3.533033  4.410650  5.446892   6.468964   8.405156   
7   0.000000  0.486633  2.560113  3.437762  4.473614   5.495941   7.440721   
8   0.518599  0.000000  1.561677  2.436310  3.473427   4.497171   6.443451   
9   2.525085  1.493574  0.000000  0.429875  1.467480   2.492644   4.463771   
10  3.465481  2.433809  0.499402  0.000000  0.527884   1.554218   3.540493   
11  4.497042  3.465439  1.530986  0.521601  0.000000   0.523013   2.556065   
12  5.342058  4.310497  2.376017  1.366597  0.341276   0.000000   1.788666   
13  7.901132  6.863255  4.941781  3.928417  2.923256   2.273971   0.000000   
14  7.782154  6.746808  4.815043  3.790372  2.766326   2.077512   0.492253   

           14  
0    0.703212  
1   12.250335  
2    5.430658  
3   11.253792  
4   10.383930  
5    9.382000  
6    8.406976  
7    7.441895  
8    6.444094  
9    4.461567  
10   3.531133  
11   2.517604  
12   1.686975  
13   0.444277  
14   0.000000

（因此，第一行包含到centroid 列中所有点的距离，包括第一个点）。

我真正想要的是将此矩阵合并到数据框，并且列名是来自GEO 的ids。

现在，我知道如何合并了：

new = GEO.merge(GEO_distances, on=['index'])

index         id                                      geometry_zone  \
0       0    A001DFD  POLYGON ((48.08793 50.93755, 48.08793 49.18650...   
1       1     A001DG  POLYGON ((60.96434 49.05222, 59.86796 49.29929...   
2       2  A001DS007  POLYGON ((53.16200 50.20131, 52.84363 48.45026...   
3       3   A001DS01  POLYGON ((59.04953 49.34561, 58.77158 47.52346...   
4       4   A001DS02  POLYGON ((58.12301 49.46915, 57.79873 47.67788...   
5       5   A001DS03  POLYGON ((57.07498 49.66937, 56.79702 47.84722...   
6       6   A001DS04  POLYGON ((56.13302 49.80835, 55.83962 48.00164...   
7       7   A001DS05  POLYGON ((55.16017 49.93189, 54.89766 48.18694...   
8       8   A001DS06  POLYGON ((54.14099 50.05542, 53.86304 48.27959...   
9       9   A001DS08  POLYGON ((52.22678 50.36050, 51.94821 48.52985...   
10     10   A001DS09  POLYGON ((50.93339 48.70894, 51.96811 48.52985...   
11     11   A001DS10  POLYGON ((50.23695 50.67887, 49.91857 48.84823...   
12     12   A001DS11  POLYGON ((50.23695 50.67887, 49.60020 50.75847...   
13     13   A001FS01  POLYGON ((46.47617 48.94772, 46.47617 47.63443...   
14     14   A001FS02  POLYGON ((46.49606 50.04213, 46.47617 48.94772...   

                     centroid          0          1         2          3  \
0   POINT (48.75295 49.98494)   0.000000  11.063874  4.299228  10.275246   
1   POINT (60.27696 48.21993)  10.983097   0.000000  6.348082   0.616036   
2   POINT (53.49869 49.22928)   4.132203   6.259105  0.000000   5.469828   
3   POINT (59.29040 48.38586)   9.982697   0.409114  5.348195   0.000000   
4   POINT (58.42620 48.49535)   9.112541   1.279148  4.477119   0.487986   
5   POINT (57.43469 48.68996)   8.102334   2.289412  3.468492   1.497509   
6   POINT (56.46528 48.82210)   7.124643   3.266993  2.490125   2.475753   
7   POINT (55.50608 48.98701)   6.151367   4.240258  1.517485   3.448859   
8   POINT (54.51093 49.10232)   5.151208   5.240246  0.515855   4.450013   
9   POINT (52.52668 49.40021)   3.145284   7.246023  0.481768   6.456493   
10  POINT (51.59314 49.51614)   2.205711   8.185458  1.420986   7.396838   
11  POINT (50.57522 49.68396)   1.174092   9.217045  2.452510   8.428427   
12  POINT (49.74105 49.81923)   0.329081  10.062023  3.297427   9.273461   
13  POINT (47.00679 48.58955)   1.235000  12.579303  5.838504  11.812993   
14  POINT (47.23437 49.55921)   0.853558  12.484730  5.717153  11.712257   

            4         5         6         7         8         9        10  \
0    9.312075  8.274448  7.312941  6.343811  5.312333  3.377798  2.368462   
1    1.399226  2.373198  3.374784  4.353762  5.318769  7.388784  8.269175   
2    4.507633  3.469029  2.507443  1.538467  0.506829  0.544190  1.416284   
3    0.399280  1.373252  2.374671  3.353424  4.318400  6.388838  7.269062   
4    0.000000  0.504366  1.503677  2.482659  3.447704  5.519952  6.398068   
5    0.538514  0.000000  0.494605  1.473030  2.437971  4.509526  5.388997   
6    1.515950  0.474954  0.000000  0.494829  1.459821  3.533033  4.410650   
7    2.489192  1.448060  0.487174  0.000000  0.486633  2.560113  3.437762   
8    3.488962  2.449214  1.487936  0.518599  0.000000  1.561677  2.436310   
9    5.494540  4.455695  3.494278  2.525085  1.493574  0.000000  0.429875   
10   6.433798  5.396039  4.434327  3.465481  2.433809  0.499402  0.000000   
11   7.465334  6.427628  5.465988  4.497042  3.465439  1.530986  0.521601   
12   8.310263  7.272662  6.311059  5.342058  4.310497  2.376017  1.366597   
13  10.830385  9.818336  8.852372  7.901132  6.863255  4.941781  3.928417   
14  10.730567  9.711458  8.743639  7.782154  6.746808  4.815043  3.790372   

          11         12         13         14  
0   1.343153   0.675055   1.051959   0.703212  
1   9.305375  10.325337  12.247130  12.250335  
2   2.454398   3.479383   5.430826   5.430658  
3   8.304972   9.325272  11.250890  11.253792  
4   7.434796   8.456133  10.381205  10.383930  
5   6.424600   7.445701   9.379809   9.382000  
6   5.446892   6.468964   8.405156   8.406976  
7   4.473614   5.495941   7.440721   7.441895  
8   3.473427   4.497171   6.443451   6.444094  
9   1.467480   2.492644   4.463771   4.461567  
10  0.527884   1.554218   3.540493   3.531133  
11  0.000000   0.523013   2.556065   2.517604  
12  0.341276   0.000000   1.788666   1.686975  
13  2.923256   2.273971   0.000000   0.444277  
14  2.766326   2.077512   0.492253   0.000000

但是，如何以简单的方式为该列指定 id 名称？手动重命名 18 000 列并不是我想的一个有趣的下午。

【问题讨论】：

标签： python-3.x pandas geopandas

【解决方案1】：

我已经找到了我的问题的答案，但我仍然想知道是否有更好、更优雅的方法来做到这一点（例如即时）。我所做的是：

new_column_name = GEO.id.to_list()
columnlist = GEO_distances.columns.to_list()
cols_remove = ['index','id','geometry_zone','centroid']
old_column_names = [x for x in columnlist if (x not in cols_remove)]

col_rename_dict = {i:j for i,j in zip(old_column_names,new_column_name)}
GEO_distances.rename(columns=col_rename_dict, inplace=True)

给出：

index         id                                      geometry_zone  \
0         0    A001DFD  POLYGON ((48.08793 50.93755, 48.08793 49.18650...   
1         1     A001DG  POLYGON ((60.96434 49.05222, 59.86796 49.29929...   
2         2  A001DS007  POLYGON ((53.16200 50.20131, 52.84363 48.45026...   
3         3   A001DS01  POLYGON ((59.04953 49.34561, 58.77158 47.52346...   
4         4   A001DS02  POLYGON ((58.12301 49.46915, 57.79873 47.67788...   
...     ...        ...                                                ...   
1790   1790     R13C1G  POLYGON ((63.72846 54.07087, 61.04155 54.02454...   
1791   1791     R13D1A  POLYGON ((63.03727 60.43190, 65.27641 57.78312...   
1792   1792     R13D1D  POLYGON ((68.90781 67.16844, 68.95414 60.51294...   
1793   1793     R13D1F  POLYGON ((61.42043 67.16403, 75.48019 67.22166...   
1794   1794     R13D1G  POLYGON ((61.40300 67.15300, 61.43388 63.43148...   

                       centroid    A001DFD     A001DG  A001DS007   A001DS01  \
0     POINT (48.75295 49.98494)   0.000000  11.063874   4.299228  10.275246   
1     POINT (60.27696 48.21993)  10.983097   0.000000   6.348082   0.616036   
2     POINT (53.49869 49.22928)   4.132203   6.259105   0.000000   5.469828   
3     POINT (59.29040 48.38586)   9.982697   0.409114   5.348195   0.000000   
4     POINT (58.42620 48.49535)   9.112541   1.279148   4.477119   0.487986   
...                         ...        ...        ...        ...        ...   
1790  POINT (62.36165 51.28081)  12.814471   2.630419   8.337061   3.267367   
1791  POINT (69.85889 59.16021)  21.991462  13.464194  18.191827  14.124815   
1792  POINT (72.22137 63.86261)  26.206982  18.602918  22.776510  19.187716   
1793  POINT (68.46954 68.61039)  26.045757  20.948750  23.468535  21.237352   
1794  POINT (65.33358 63.93216)  20.589210  15.508162  17.853344  15.717912   

       A001DS02   A001DS03   A001DS04   A001DS05   A001DS06   A001DS08  \
0      9.312075   8.274448   7.312941   6.343811   5.312333   3.377798   
1      1.399226   2.373198   3.374784   4.353762   5.318769   7.388784   
2      4.507633   3.469029   2.507443   1.538467   0.506829   0.544190   
3      0.399280   1.373252   2.374671   3.353424   4.318400   6.388838   
4      0.000000   0.504366   1.503677   2.482659   3.447704   5.519952   
...         ...        ...        ...        ...        ...        ...   
1790   3.862726   4.616091   5.526811   6.415345   7.329588   9.280236   
1791  14.623171  15.220831  15.921820  16.621702  17.363742  18.956701   
1792  19.622822  20.146582  20.757196  21.374153  22.035882  23.454339   
1793  21.458123  21.751888  22.104256  22.496392  22.947829  23.939341   
1794  15.894837  16.153433  16.481252  16.864660  17.318735  18.347265

欢迎任何其他更有效的解决方案。

【讨论】：