Python - 将 CSV 导入为 DataFrame，使用 groupby 过滤并将结果导出为格式化文本

Question

I'm struggling behind a python script to import a formatted CSV ("," as delimiter) as DataFrame, group the result by value in specific column and based on that groups I need to output a formatted CLI config script for a network device.

I would be very happy if someone could help me

My CSV (users.csv) is something like this

user,email,group
pippo1,pippo1@corporate.com,grp1
pippo2,pippo2@corporate.com,grp1
pippo10,pippo10@corporate.com,grp2
user10,user10@corporate.com,grp3
user93,user93@corporate.com,grp1

Now I'm able to import and group data by "group" column with

 df = pd.read_csv('users.csv', sep=',') grouped = df.groupby('group')

What I'm not able to do is to produce a text output like this

Intro
edit grp1
append member pippo1 pippo2 user93
next
edit grp2
append member pippo10
next
edit grp3
append member user10
next
end

With the "for" below I get this result and unfortunately is not what I'm trying to achieve

 for group in grouped: print (group) grp = group[0] usergrp_text += "edit " + grp usertoappend = group[1] print (usertoappend['user'].to_string(index=False))

print of group variable

('grp1',      user                        email group  0  pippo1       pippo1@corporate.com  grp1  1  pippo2   pippoilbello@corporate.com grp1 4  user93  uservalgopoco@corporate.com  grp1)

print of group[1] variable

pippo1 pippo2 user93

Answer 1

When doing for group in grouped in reality you are getting a tuple with groupname,groupcontents.

Use the groupname for the edit and expand the users with a comprehension of the user field of the "sub-dataframe". Not the most efficient, but gets the job done

grouped = df.groupby('group')
print("Intro")
for k,g in grouped:
    print(f"edit {k}")
    print(f"append member {' '.join([x for x in g.user])}")
    print("next")
print("end")

Prints:

Intro
edit grp1
append member pippo1 pippo2
next
edit grp2
append member pippo10
next
edit grp3
append member user10
next
end