인프런 커뮤니티 질문&답변

안녕하세요.

아래 코드에서 마지막 부분에서 에러가 발생하는데 찾아봐도 해결을 못하겠습니다.

# 최종 데이터 합치기

df1 = pd.concat(df, ignore_index=True)

---------------------------------------------------------------------------
InvalidIndexError                         Traceback (most recent call last)
Cell In[89], line 2
      1 # 최종 데이터 합치기    
----> 2 df1 = pd.concat(df, ignore_index=True)

File ~\anaconda3\Lib\site-packages\pandas\core\reshape\concat.py:393, in concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
    378     copy = False
    380 op = _Concatenator(
    381     objs,
    382     axis=axis,
   (...)
    390     sort=sort,
    391 )
--> 393 return op.get_result()

File ~\anaconda3\Lib\site-packages\pandas\core\reshape\concat.py:676, in _Concatenator.get_result(self)
    674         obj_labels = obj.axes[1 - ax]
    675         if not new_labels.equals(obj_labels):
--> 676             indexers[ax] = obj_labels.get_indexer(new_labels)
    678     mgrs_indexers.append((obj._mgr, indexers))
    680 new_data = concatenate_managers(
    681     mgrs_indexers, self.new_axes, concat_axis=self.bm_axis, copy=self.copy
    682 )

File ~\anaconda3\Lib\site-packages\pandas\core\indexes\base.py:3875, in Index.get_indexer(self, target, method, limit, tolerance)
   3872 self._check_indexing_method(method, limit, tolerance)
   3874 if not self._index_as_unique:
-> 3875     raise InvalidIndexError(self._requires_unique_msg)
   3877 if len(target) == 0:
   3878     return np.array([], dtype=np.intp)

InvalidIndexError: Reindexing only valid with uniquely valued Index objects

============================

df = []

articleNos = ['2433459189','2433504511']

for articleNo in articleNos:

ind_url = f'https://new.land.naver.com/api/articles/{articleNo}?complexNo='

res = requests.get(ind_url, headers=headers)

ind_dict = res.json()

article_df = pd.Series(ind_dict['articleDetail']).to_frame().T

# articleDetail_df = articleDetail_df[['articl/eNo','articleName','buildingTypeName','realestateTypeName', 'tradeTypeName', 'cityName','divisionName', 'sectionName', 'etcAddress', 'monthlyManagementCost', 'buildingName']]

if 'articleFloor' in ind_dict.keys():

articleFloor_df = pd.Series(ind_dict['articleFloor']).to_frame().T

article_df = pd.concat(

[

article_df,

articleFloor_df,

],

axis=1

)

else:

print(articleNo, '/', 'articleFloor')

# articleFloor_df = articleFloor_df[['totalFloorCount','correspondingFloorCount']]

if 'articlePrice' in ind_dict.keys():

articlePrice = pd.Series(ind_dict['articlePrice']).to_frame().T

article_df = pd.concat(

[

article_df,

articlePrice,

],

axis=1

)

else:

print(articleNo, '/', 'articlePrice')

# articlePrice_df = articlePrice_df[['dealPrice','allWarrantPrice','allRentPrice']]

if 'articleRealtor' in ind_dict.keys():

articleRealtor = pd.Series(ind_dict['articleRealtor']).to_frame().T

article_df = pd.concat(

[

article_df,

articleRealtor,

],

axis=1

)

else:

print(articleNo, '/', 'articleRealtor')

# articleRealtor_df = articleRealtor_df[['realtorName','representativeName','cellPhoneNo','representativeTelNo']]

if 'articleSpace' in ind_dict.keys():

articleSpace = pd.Series(ind_dict['articleSpace']).to_frame().T

article_df = pd.concat(

[

article_df,

articleSpace,

],

axis=1

)

else:

print(articleNo, '/', 'articleSpace')

# articleSpace_df = articleSpace_df[['supplySpace','exclusiveSpace']]

# article_df = pd.concat(

# [

# articleDetail_df,

# articleFloor_df,

# articlePrice_df,

# articleRealtor_df,

# articleSpace_df,

# ],

# axis=1

# )

df.append(article_df)

# 최종 데이터 합치기

df1 = pd.concat(df, ignore_index=True)