pandas，如果行包含通配符文本，则合并重复项

Question

我有一个重复项的数据集 ( ID)。数据集包含信息和电子邮件。我正在尝试连接电子邮件（如果行有字符@），然后删除重复项。

如何附加仅包含电子邮件地址的行？@我认为我可以通过使用通配符并替换这部分来 跳过附加包含字符的所有行

if row['Store1_Email']: # <- not working

对于任何这些尝试，但没有任何效果：

1.

if str('**@**') in row['Store1_Email']: # <- not working

错误：

Traceback (most recent call last):

  File "g:/Till/till_duplicate.py", line 35, in <module>

    if str('**@**') in row['Store1_Email']:

TypeError: argument of type 'float' is not iterable

PS G:\Till>

错误：

Traceback (most recent call last):

  File "g:/Till/till_duplicate.py", line 35, in <module>

    if df_merged_duplicates[df_merged_duplicates.loc[i, 'Store1_Email'].str.contains('@')]:

AttributeError: 'str' object has no attribute 'str'

PS G:\Till>

Answer 1

我会使用“拆分-应用-组合”的方法。在 pandas 中，您可以使用该groupby函数来执行此操作，然后应用一个函数将电子邮件地址组合到每个组中（在这种情况下，您可以按 col 进行分组）ID。我编写了一个函数来组合给定列的电子邮件地址：def combine_emails(series):&nbsp; &nbsp; strs = [s for s in series.astype(str).values if '@' in s]&nbsp; &nbsp; combined_emails = ",".join(strs)&nbsp; &nbsp; if combined_emails !='':&nbsp; &nbsp; &nbsp; &nbsp; return combined_emails&nbsp; &nbsp; else:&nbsp; &nbsp; &nbsp; &nbsp; return np.nan然后，我编写了一个函数来获取每个分组数据帧的第一行，并调用电子邮件列上的组合函数来填充行电子邮件值：def combine_duplicate_rows(df):&nbsp; &nbsp; first_row = df.iloc[0]&nbsp; &nbsp; for email_col in ['Store1_Email', 'Store2_Email', 'Store3_Email', 'Store4_Email']:&nbsp; &nbsp; &nbsp; &nbsp; first_row[email_col] = combine_emails(df[email_col])&nbsp; &nbsp; return first_row然后您可以将其应用combine_duplicate_rows到您的组中并获得解决方案：In [71]: df.groupby('ID').apply(combine_duplicate_rows)Out[71]:&nbsp; &nbsp; ID Header 1&nbsp; Header 2&nbsp; Header 3&nbsp; Header 4&nbsp; Header 5&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Store1_Email&nbsp; Header 9&nbsp; Store2_Email&nbsp; Header 12&nbsp; Store3_Email&nbsp; Header 17&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Store4_EmailID1&nbsp; &nbsp; 1&nbsp; &nbsp; &nbsp; &nbsp;AA&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;[e-mail]&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; [e-mail]2&nbsp; &nbsp; 2&nbsp; &nbsp; &nbsp; &nbsp;BB&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN3&nbsp; &nbsp; 3&nbsp; &nbsp; &nbsp; &nbsp;CC&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN4&nbsp; &nbsp; 4&nbsp; &nbsp; &nbsp; &nbsp;DD&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN5&nbsp; &nbsp; 5&nbsp; &nbsp; &nbsp; &nbsp;EE&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; [e-mail],[e-mail]&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN6&nbsp; &nbsp; 6&nbsp; &nbsp; &nbsp; &nbsp;FF&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; [e-mail],[e-mail]&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN7&nbsp; &nbsp; 7&nbsp; &nbsp; &nbsp; &nbsp;GG&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN8&nbsp; &nbsp; 8&nbsp; &nbsp; &nbsp; &nbsp;HH&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN9&nbsp; &nbsp; 9&nbsp; &nbsp; &nbsp; &nbsp;II&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; [e-mail]10&nbsp; 10&nbsp; &nbsp; &nbsp; &nbsp;JJ&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN11&nbsp; 11&nbsp; &nbsp; &nbsp; &nbsp;KK&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; [e-mail]12&nbsp; 12&nbsp; &nbsp; &nbsp; &nbsp;LL&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; [e-mail],[e-mail]&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN13&nbsp; 13&nbsp; &nbsp; &nbsp; &nbsp;MM&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN14&nbsp; 14&nbsp; &nbsp; &nbsp; &nbsp;NN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;NaN&nbsp; &nbsp; &nbsp; &nbsp; NaN&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; NaN然后你就会有一个重复的ID列，但你可以删除它del df['ID']