[英]Count unique elements and sum up values in a pandas groupby operation
I have a table with the follows data: 我有一个包含以下数据的表:
day concept click item_id
2015-05-01 A 6 s4P~Hzs1w5R12Dpyn2IK
B 6 s4P~Hzs1w5R12Dpyn2IK
C 1 DOwfmfFvdEIZ1IdXqTiu
D 1 wPaYuIh~t8y7rU3HP43N
D 7 Ya_M~2N6eX0kem8IgdSp
And I want obtain the count of distint item_id and sum click for all item_id daily , for example: 我想要获取distint item_id的计数,并每天获取所有item_id的总点击次数,例如:
day concept click count_item_id
2015-05-01 A 6 1
B 6 1
C 1 1
D 8 2
I work with Python and Pandas library 我使用Python和Pandas库
Use a groupby
followed by an agg
: 使用groupby
后跟agg
:
df.groupby(['day', 'concept']).agg({'click' : 'sum', 'item_id' : 'count'})
item_id click
day concept
2015-05-01 A 1 6
B 1 6
C 1 1
D 2 8
请检查这是否是您想要的:
df[['day', 'concept']].groupby(['click', 'item_id']).agg(['sum', 'count'])
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