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
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 5groupby
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)Copyright © 2021 Codeinu
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