合并python数据框和嵌套列表

Question

无法使用where条件组合/合并/交叉联接数据框和嵌套列表（如果嵌套列表中最接近的zip等于实际zip，则不显示在最接近的zip字段中）以获得所需的输出。

我到目前为止的代码

x=0
print(test_df)
print(type(test_df))
for x in range(5):      
 nearest_result=search.by_coordinates(test_df.iloc[x,1],test_df.iloc[x,2], radius=30,returns=3)
n_zip=[res.zipcode for res in nearest_result]
print(n_zip)
print(type(n_zip))

数据框和嵌套列表：

所需的输出：

Answer 1

也许可以提出一个更简单的方法，但是作为第一步，首先删除“ NEAREST_ZIP”：

>>> print(test_df)  # /!\ dropped 'NEAREST_ZIP
ID  BEGIN_LAT  BEGIN_LON  ZIP_CODE
0   0    30.9958   -87.2388     36441
1   1    42.5589   -92.5000     50613
2   2    42.6800   -91.9000     50662
3   3    37.0800   -97.8800     67018
4   4    37.8200   -96.8200     67042
>>> # used nzip:
>>> nzip = [[36441, 32535, 36426],
             [50613, 50624, 50613],  # i guess there was a typo in your code here
             [50662, 50641, 50671],
             [67018, 67003, 67049],
             [67042, 67144, 67074]]

>>> # build a `closest` dataframe:
>>> closest = pd.DataFrame(data={k: (v1, v2) for k, v1, v2 in nzip}).T.stack().reset_index().drop(columns=['level_1'])
>>> closest.columns = ['ZIP_CODE', 'NEAREST_ZIP']
>>> # merging
>>> test_df.merge(closest)
   ID  BEGIN_LAT  BEGIN_LON  ZIP_CODE  NEAREST_ZIP
0   0    30.9958   -87.2388     36441        32535
1   0    30.9958   -87.2388     36441        36426
2   1    42.5589   -92.5000     50613        50624
3   1    42.5589   -92.5000     50613        50613
4   2    42.6800   -91.9000     50662        50641
5   2    42.6800   -91.9000     50662        50671
6   3    37.0800   -97.8800     67018        67003
7   3    37.0800   -97.8800     67018        67049
8   4    37.8200   -96.8200     67042        67144
9   4    37.8200   -96.8200     67042        67074