Pandas：计算两列的不同组合并添加到Same Dataframe

Question

需要帮助将两列的唯一组合添加到pandas中的同一数据框中。 我想要那个“nos”专栏。

Input:
id  acct_nos name
1   1a       one
1   1a       two
2   2b       three
3   3a       four
3   3b       five
3   3c       six
3   3d       seven

这是我想要的输出：

Output:
id  acct_nos    nos name
1   1a          1   one 
1   1a          1   two
2   2b          1   three
3   3a          4   four
3   3b          4   five
3   3c          4   six
3   3d          4   seven

在上面的例子中 Id = 1只有1个acct_nos-1a，因此nos必须具有值1。 Id = 3只有4个acct_nos-3a到3d，因此nos必须具有值4。

不确定如何将它放在Python Pandas中。我可以搞清楚的SQL查询。

由于

Answer 1

您可以Environment: Request Method: GET Request URL: http://127.0.0.1:8000/admin/test%3D5/ Django Version: 1.10.5 Python Version: 2.7.12 Installed Applications: ['alexbase', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'easy_thumbnails'] Installed Middleware: ['django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware'] Traceback: File "/home/user/.local/lib/python2.7/site-packages/django/core/handlers/exception.py" in inner 39. response = get_response(request) File "/home/user/.local/lib/python2.7/site-packages/django/core/handlers/base.py" in _get_response 187. response = self.process_exception_by_middleware(e, request) File "/home/user/.local/lib/python2.7/site-packages/django/core/handlers/base.py" in _get_response 185. response = wrapped_callback(request, *callback_args, **callback_kwargs) File "/home/user/.local/lib/python2.7/site-packages/django/contrib/auth/decorators.py" in _wrapped_view 23. return view_func(request, *args, **kwargs) Exception Type: TypeError at /admin/test=5/ Exception Value: object() takes no parameters 使用groupby.transform功能计算每个 id 的唯一元素数量：

nunique()

Answer 2

选项1

df.assign(nos=df.id.map(df.drop_duplicates(['id', 'acct_nos']).id.value_counts()))

选项2
使用Counter

from collections import Counter

tups = pd.unique(
    zip(df.id.values.tolist(), df.acct_nos.values.tolist())
).tolist()
df.assign(nos=df.id.map(Counter([tup[0] for tup in tups])))

   id acct_nos   name  nos
0   1       1a    one    1
1   1       1a    two    1
2   2       2b  three    1
3   3       3a   four    4
4   3       3b   five    4
5   3       3c    six    4
6   3       3d  seven    4