我正在嘗試做一些類似于如何循環(huán)遍歷 pandas df 列我的初始數(shù)據(jù)框logs包含以下內(nèi)容：ID DB  USER  MDX_TEXT1  DB1  JOE  SELECT [ATTR1].[ATTR1].[THE_ATTR1] ON COLUMNS,[ATTR2].[ATTR2].[THE_ATTR2] ON ROWS FROM [THE_DB] WHERE [ATTR3].[ATTR3].[THE_ATTR3]2  DB1  JAY  SELECT [ATTR1].[ATTR1].[THE_ATTR1] ON COLUMNS, [ATTR3].[ATTR3].[THE_ATTR3] ON ROWS FROM [THE_DB] WHERE [ATTR3].[ATTR3].[THE_ATTR3]MDX_TEXT使用正則表達(dá)式，然后我提取每個(gè)的唯一實(shí)例ID# Step 1: Define a pattern to extract MDX regex patternimport repattern = re.compile (r'(\[[\w ]+\]\.\[[\w ]+\](?:\.(?:Members|\[Q\d\]))?)')# Step 2: Create a dataframe to store distinct list of MDX Query attributes, based on patternextrpat =  (            logs['MDX_TEXT'].str.extractall(pattern)                            .drop_duplicates()                            .to_numpy()           )# Step 3: Create a dataframe to store distinct list of attributes used in a queryattr= pd.DataFrame(data=extrpat)attr.rename({0: 'attrname'}, inplace=True, axis=1)# Preview the first 5 lines of the attributes dataframeattr.head()結(jié)果是：attrname[THE_ATTR1][THE_ATTR2][THE_ATTR3][THE_ATTR1][THE_ATTR3]我想要的是，除了在步驟 2 中提取唯一屬性之外，還提取IDand USER，如下所示：ID  USER  attrname1  JOE  [THE_ATTR1]1  JOE  [THE_ATTR2]1  JOE  [THE_ATTR3]2  JAY  [THE_ATTR1]2  JAY  [THE_ATTR3]最后，加入attr和logs上的數(shù)據(jù)框ID。這個(gè)想法是引入第三個(gè)數(shù)據(jù)框users：USER  LOCJOE  NYJIL  NJMAC  CA......我將加入上述內(nèi)容USER以結(jié)束：ID  USER  LOC  attrname1  JOE  NY  [THE_ATTR1]1  JOE  NY  [THE_ATTR2]1  JOE  NY  [THE_ATTR3]2  JAY  NJ  [THE_ATTR1]2  JAY  NJ  [THE_ATTR3]