Answers for "dataframe.groupby"

pandas new df from groupby

df = pd.DataFrame(old_df.groupby(['groupby_attribute'])['mean_attribute'].mean())
df = df.reset_index()
df

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

groupby in pandas

>>> df = pd.DataFrame({'Animal': ['Falcon', 'Falcon',
...                               'Parrot', 'Parrot'],
...                    'Max Speed': [380., 370., 24., 26.]})
>>> df
   Animal  Max Speed
0  Falcon      380.0
1  Falcon      370.0
2  Parrot       24.0
3  Parrot       26.0
>>> df.groupby(['Animal']).mean()
        Max Speed
Animal
Falcon      375.0
Parrot       25.0

pandas groupby

data.groupby('month', as_index=False).agg({"duration": "sum"})

dataframe, groupby, select one

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

groupby

df.groupby(sepal_len_groups)['sepal length (cm)'].agg(count='count')

sum_sep = sep.groupby('Year').agg({'TotalProjects':'sum',
                                   'TotalFunds':'sum',
                                   'TotalFunds':'count',
                                   'SubDistrict':'count'})
                                   
sum_sep.stb.subtotal(grand_label='Total').applymap('{:,.0f}'.format)