Which of the following method can be applied on a groupby object to get the group details? code example

Example 1: dataframe, groupby, select one

df.sort_values('date').groupby(['id', 'period', 'type']).first()

Example 2: group by pandas examples

>>> n_by_state = df.groupby("state")["state"].count()
>>> n_by_state.head(10)
state
AK     16
AL    206
AR    117
AS      2
AZ     48
CA    361
CO     90
CT    240
DC      2
DE     97
Name: last_name, dtype: int64

Example 3: Groups the DataFrame using the specified columns

# Groups the DataFrame using the specified columns

df.groupBy().avg().collect()
# [Row(avg(age)=3.5)]
sorted(df.groupBy('name').agg({'age': 'mean'}).collect())
# [Row(name='Alice', avg(age)=2.0), Row(name='Bob', avg(age)=5.0)]
sorted(df.groupBy(df.name).avg().collect())
# [Row(name='Alice', avg(age)=2.0), Row(name='Bob', avg(age)=5.0)]
sorted(df.groupBy(['name', df.age]).count().collect())
# [Row(name='Alice', age=2, count=1), Row(name='Bob', age=5, count=1)]

Example 4: pandas print groupby

grp = df.groupby['colName']
grp.describe()