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: int64group 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: int64groupby 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 25.0pandas groupby
data.groupby('month', as_index=False).agg({"duration": "sum"})pandas group by column
>> df = pd.read_excel(r"C:\path_to_file\dataset_test.xlsx")
>> print(df)
'''
name number
0 p1 64
1 p2 98
2 p1 93
3 p2 57
4 p1 89
5 p2 83
6 p1 58
7 p2 73
8 p1 64
9 p2 24
'''
>> data = df.groupby("name").number.apply(list)
>> print(data)
'''
name
p1 [64, 93, 89, 58, 64]
p2 [98, 57, 83, 73, 24]
Name: number, dtype: object
'''
>> print(data.p1)
'''
[64, 93, 89, 58, 64]
'''python group by
df.groupby('group').assign(mean_var1 = lambda x: np.mean(x.var1)groupby
df['frequency'] = df['county'].map(df['county'].value_counts())
county frequency
1 N 5
2 N 5
3 C 1
4 N 5
5 S 1
6 N 5
7 N 5Copyright © 2021 Codeinu
Forgot your account's password or having trouble logging into your Account? Don't worry, we'll help you to get back your account. Enter your email address and we'll send you a recovery link to reset your password. If you are experiencing problems resetting your password contact us
