>>> from pandas import Series, DataFrame
>>> import pandas as pd
>>> df = pd.DataFrame({'class': ['A', 'B', 'C'], 'count':[1,0,2]})
>>> print(df)
   class  count
0     A      1
1     B      0
2     C      2

>>> for group in df.groupby('class', group_keys = True):
>>>     print(group)
('A',   class  count
0     A      1)
('B',   class  count
1     B      0)
('C',   class  count
2     C      2)

>>> def checkit(group):
>>>     print(group)
>>> df.groupby('class', group_keys = True).apply(checkit)
  class  count
0     A      1
  class  count
0     A      1
  class  count
1     B      0
  class  count
2     C      2

>>> def addone(group):
>>>     group['count'] += 1
>>>     return group

>>> df.groupby('class', group_keys = True).apply(addone)
>>> print(df)

      class  count
0     A      1
1     B      0
2     C      2

class  count
0     A      2
1     B      1
2     C      3

guestid,keyword
1,null
2,null
2,null
3,null
3,null
3,null
4,null
4,null
4,null
4,null

df=pd.read_csv("log_sample.csv")
grouped = df.groupby("guestid")

for guestid, df_group in grouped:
    print(list(df_group['guestid']))

df.head(100)

[1]
[2, 2]
[3, 3, 3]
[4, 4, 4, 4]

df = pd.DataFrame({"a": ["x", "y"], "b": [1, 2]})

def func(group):
    print(group.name)
    return group

df.groupby('a').apply(func)
x
y

   a  b
0  x  1
1  y  2

df.groupby('a').apply(func)
x
x
y

   a  b
0  x  1
1  y  2