python - Select Row by Username with Pandas

Question

I have a Table with multiple users and the data belonging to them.

Now I want to create separate tables for each user like this:

Each account belonging to the users has a different ID so I can't use the ID to select.

How can I select the all Rows belonging to one specific name in the "User" row and then create separate table?

Also I would like take data out of a column and sort it into two new columns.

One example would be something like the email like: [e-mail] and split it at the dot and create two new Columns "Name" and "Surname".

标签： pythonexcelpython-3.xpandaspython-2.7

Answer 1

分解方式 User

df.groupby('User').get_group('John')

   ID  User                  Email
0   1  John  [e-mail]
1   2  John  [e-mail]
2   3  John  [e-mail]

也可以循环执行

grp = df.groupby('User')

for group in grp.groups:
    print(grp.get_group(group))

                   Email  ID   User
3  [e-mail]   4  David
4  [e-mail]   5  David
                   Email  ID  User
5  [e-mail]   6  Fred
                   Email  ID  User
0  [e-mail]   1  John
1  [e-mail]   2  John
2  [e-mail]   3  John

---

拆分 Email 列

email_df = df['Email'].str.split(r'(.+)\.(.+)@', expand=True)]
pd.concat([df, email_df], axis=1)

                   Email  ID   User      0       1          2
0  [e-mail]   1   John   john  tomson  email.com
1  [e-mail]   2   John   john  tomson  email.com
2  [e-mail]   3   John   john  tomson  email.com
3  [e-mail]   4  David  david   matty  email.com
4  [e-mail]   5  David  david   matty  email.com
5  [e-mail]   6   Fred   fred  brainy  email.com